Foto profilo

Filippo Stanco - Ph.D.

Professore ordinario di INF/01
Presidente del Corso di Laurea in Informatica (I livello)
Delegato del Rettore per le innovazioni tecnologiche per l'informazione e la comunicazione.

Contatti
E-mail filippo.stanco@unict.it
Telefono +39 095 738 3051
Fax +39 095 33 00 94
Indirizzo Dipartimento di Matematica e Informatica
Viale A. Doria, 6 - 95125 Catania
Stanza 369
Personal site http://web.dmi.unict.it/docenti/filippo.stanco
Archeomatica https://archeomatica.unict.it/
IPLab https://iplab.dmi.unict.it/
Skills
Didattica Ricerca Beni Culturali Immagini Digitali Giochi Digitali Danger
Informazioni personali
Experience

Professore Ordinario

Università degli Studi di Catania
Settore scientifico-disciplinare INF/01 – Informatica, Dipartimento di Matematica ed Informatica.

2023 - Oggi


Experience

Presidente CdL Informatica

Università degli Studi di Catania
Presidente del Corso di Laurea triennale in Informatica per il quadriennio 2021/25.

2021 - Oggi


Experience

Delegato del Rettore

Università degli Studi di Catania
Delegato del Rettore per "Innovazioni tecnologiche per l’informazione e la comunicazione".

2019 - Oggi


Experience

Professore Associato

Università degli Studi di Catania
Settore scientifico-disciplinare INF/01 – Informatica, Dipartimento di Matematica ed Informatica.

2014 - 2023


Experience

Ricercatore

Università degli Studi di Catania
Settore scientifico-disciplinare INF/01 – Informatica, Dipartimento di Matematica ed Informatica.

2006 - 2014


Experience

Assegnista di Ricerca

Università degli Studi di Catania
Settore scientifico-disciplinare INF/01 - Informatica, sul tema “Elaborazione delle Immagini e grafica computerizzata”.

2005 - 2006


Experience

Assegnista di Ricerca

Università di Trieste
Settore scientifico-disciplinare ING-INF/01 - Elettronica, sul tema “Sviluppo di un sistema di restauro per stampe fotografiche d’epoca (SIRAD)”.

2003 - 2005


Education

Dottorato di Ricerca in Informatica, XV ciclo

Università degli Studi di Catania
Tesi: "Image Enhancement Techniques: Zooming and Super Resolution".
Tutor: Prof. Giovanni Gallo.

2003


Education

Laurea in Scienze dell’Informazione, votazione di 110/110 e Lode

Università degli Studi di Catania
Tesi: "Apprendimento automatico di pattern grafici".
Relatore: Prof. Giovanni Gallo. Correlatore: Dott. Sebastiano Battiato

1999


Short bio


Filippo Stanco, nato nel 1975, è oggi Professore Ordinario di Informatica presso il Dipartimento di Matematica e Informatica dell’Università di Catania. Dal 2017 ad oggi (secondo mandato) è Presidente del corso di laurea triennale in Informatica. È delegato del Rettore per le “Innovazioni tecnologiche per l’informazione e la comunicazione” (dal 2019). I suoi interessi di ricerca includono l'analisi e il trattamento di dati multimediali con riferimento a specifici settori applicativi e di natura interdisciplinare (Image Processing, Applicazioni Mediche, Serious Game). Dal 2007 è responsabile del gruppo di ricerca Archeomatica, centro di competenza volto allo sviluppo di soluzioni innovative e applicazioni in ambito Cultural Heritage realizzate anche nell’ambito di progetti di ricerca nazionale o internazionali, in collaborazione con enti, istituzioni pubbliche e private.

Didattica


  • Multimedia e Laboratorio: modulo multimedia (6 CFU), A.A. 2016-2017, 2017-18, 2018-19, 2019-20, 2020-21, 2021-22 corso di Laurea Magistrale in Informatica, Università di Catania;;
  • Multimedia e Laboratorio: modulo laboratorio (3 CFU), A.A. 2022-23 corso di Laurea Magistrale in Informatica, Università di Catania;;
  • Sviluppo di Giochi Digitali – Digital Game development (6 CFU), A.A. 2015-2016, 2016-2017, 2017-18, 2018-19, 2019-20, 2020-21, 2021-22, 2022-23 corso di Laurea in Informatica, Università di Catania;;
  • Interazione e Multimedia (9 CFU), A.A. 2009-2010, 2010-2011, 2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, 2016-2017, 2017-18 corso di Laurea in Informatica, Università di Catania;;
  • Interazione e Multimedia e Laboratorio: modulo di Interazione e Multimedia e modulo di laboratorio (6+3 CFU), canale M-Z, A.A. 2018-19 corso di Laurea in Informatica, Università di Catania;;
  • Interazione e Multimedia e Laboratorio: modulo di Interazione e Multimedia (6 CFU), canale A-L, A.A. 2018-19, 2019-20, 2020-21, 2021-22, 2022-23 corso di Laurea in Informatica, Università di Catania;;
  • Multimedia (9 CFU), A.A. 2013-2014, 2014-2105 corso di Laurea Magistrale in Informatica, Università di Catania;
  • C.I. di Fisica, informatica e statistica medica: Modulo di Informatica (3 CFU), A.A. 2011-2012, 2012-2013 Corso di laurea magistrale in Medicina e Chirurgia, polo B, Facoltà di Medicina e Chirurgia, Università di Catania;
  • C.I. di Fisica, statistica e informatica: Modulo di Informatica (2 CFU), A.A. 2011-2012, 2012- 2013 Corso di laurea magistrale in Infermeristica, polo A, Facoltà di Medicina e Chirurgia, Università di Catania;
  • Interazione e Multimedia (6 CFU), A.A. 2007-2008, 2008-2009 corso di Laurea in Informatica, Università di Catania;
  • Interazione e Multimedialità (6 CFU), A.A. 2005-2006, 2006-2007, corso di Laurea in Informatica Applicata, centro IPPARI, Università di Catania, sede di Comiso;
  • Introduzione ai Sistemi Informativi Territoriali - GIS (3 CFU), A.A. 2006-2007, corso di Laurea in Informatica, Università di Catania;
  • Informatica (8 CFU), A.A. 2009-2010, corso di Laurea in Tecnologie Applicate alla Conservazione ed al Restauro dei Beni Culturali, Università di Catania, sede Catania;
  • Laboratorio di Informatica I (3 CFU), A.A. 2006-2007, 2007-2008, 2008-2009, 2010-2011, corso di Laurea in Tecnologie Applicate alla Conservazione ed al Restauro dei Beni Culturali, Università di Catania, sede Siracusa;
  • Laboratorio di Informatica II (4 CFU), A.A. 2006-2007, 2007-2008, 2008-2009, corso di Laurea in Tecnologie Avanzate Applicate alla Conservazione ed al Restauro dei Beni Culturali, Università di Catania, sede Siracusa;
  • Video e Foto Editing (9 CFU), A.A. 2008-2009, 2009-2010, 2016-2017 Accademia di Belle Arti di Catania;
  • Video e Foto Editing (6 CFU), A.A. 2005-2006, 2006-2007, 2007-2008, 2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016 Accademia di Belle Arti di Catania;

Pubblicazioni


La lista delle pubblicazioni viene acquisita in maniera automatica attraverso il servizio Elsevier Scopus API. Nel caso siano presenti degli errori è possibile segnalarli a filippo.stanco@unict.it


  • 93 Articoli
  • 1057 Citazioni (in 802 documenti)
  • 146 Coautori
  • 17 H-Index
Review
Industry 4.0: Machinery integration with supply chain and logistics in compliance with Italian regulations, Sinitò D., Santarcangelo V., Stanco F., Giacalone M., MethodsX, 2023, vol. 11.
Cited by: 0
This paper shows a real overview of the interconnection and automated integration of 4.0 machinery within the supply chain or logistics of two companies in the southern Italian territory. The authors provide an exhaustive analysis of the Italian legislation and the strict requirements in order to assess which investments are part of Industry 4.0 with a focus on business risk. The work also shows the potential of a new framework developed that allows using OPC-UA and Modbus protocols to access the functional variables of the 4.0 machinery in a bidirectional way, directly from cloud applications. The proposed solutions help companies to develop more efficient production processes and to fulfil the requirements imposed by Italian regulations in order to benefit from Industry 4.0 financial aid.
Article
Beyond the state of the art of reverse vaccinology: predicting vaccine efficacy with the universal immune system simulator for influenza, Russo G., Crispino E., Maleki A., Di Salvatore V., Stanco F., Pappalardo F., BMC Bioinformatics, 2023, vol. 24.
Cited by: 0
When it was first introduced in 2000, reverse vaccinology was defined as an in silico approach that begins with the pathogen's genomic sequence. It concludes with a list of potential proteins with a possible, but not necessarily, list of peptide candidates that need to be experimentally confirmed for vaccine production. During the subsequent years, reverse vaccinology has dramatically changed: now it consists of a large number of bioinformatics tools and processes, namely subtractive proteomics, computational vaccinology, immunoinformatics, and in silico related procedures. However, the state of the art of reverse vaccinology still misses the ability to predict the efficacy of the proposed vaccine formulation. Here, we describe how to fill the gap by introducing an advanced immune system simulator that tests the efficacy of a vaccine formulation against the disease for which it has been designed. As a working example, we entirely apply this advanced reverse vaccinology approach to design and predict the efficacy of a potential vaccine formulation against influenza H5N1. Climate change and melting glaciers are critical due to reactivating frozen viruses and emerging new pandemics. H5N1 is one of the potential strains present in icy lakes that can raise a pandemic. Investigating structural antigen protein is the most profitable therapeutic pipeline to generate an effective vaccine against H5N1. In particular, we designed a multi-epitope vaccine based on predicted epitopes of hemagglutinin and neuraminidase proteins that potentially trigger B-cells, CD4, and CD8 T-cell immune responses. Antigenicity and toxicity of all predicted CTL, Helper T-lymphocytes, and B-cells epitopes were evaluated, and both antigenic and non-allergenic epitopes were selected. From the perspective of advanced reverse vaccinology, the Universal Immune System Simulator, an in silico trial computational framework, was applied to estimate vaccine efficacy using a cohort of 100 digital patients.
Conference Paper
A method to improve the color rendering accuracy in cultural heritage: Preliminary results, Allegra D., Furnari G., Gargano S., Gueli A., Parisi S., Pasquale S., Stanco F., Stella G., Journal of Physics: Conference Series, 2022, vol. 2204.
Cited by: 1
Color specification is an important challenge in many application domains including Cultural Heritage. The collection of metadata concerning Cultural Heritage involves the valorization, fruition and becomes part of the conservation process. It becomes essential to find methods that simplify and optimize the acquisition of such data as color information. In this regard, in this work we present the preliminary results of a project that involves the acquisition by 3D scanner of samples of different colors placed in a controlled environment and with different illumination conditions. To make more accurate the color rendering, the color coordinates of each sample were measured by a spectrophotometer. All the obtained measurements become part of a dataset with which to train a machine learning model that learns how to perform the transformation from the RGB to the CIELab color space in different lighting condition.
Conference Paper
Color specification for color rendering, Incardona A., Allegra D., Furnari G., Galvagno R., Rapisarda S., Stanco F., Stella G., Gueli A.M., 2022 IMEKO TC-4 International Conference on Metrology for Archaeology and Cultural Heritage, MetroArchaeo 2022, 2022, pp. 374-377.
Cited by: 0
The present work was carried out as part of the CLEAR project, which aims to create a virtual diagnostic laboratory for polychrome artifacts through the definition of an image acquisition and processing protocol with high resolution and accuracy in terms of colour rendering. To achieve this goal, contact spectrophotometric and distance spectroradiometric measurements for colour specification will be performed. All data will be used for the processing, training, and validation of a predictive model for the evaluation of colour differences and for the creation of a two-way correspondence between RGB colour values and coordinates expressed in the CIELAB colour space. On this occasion, the results obtained on a first series of laboratory specimens consisting of monochrome cubes to highlight the influence of the contact and distance measurements on the calculation of the RGB triplet are discussed.
Conference Paper
Natural Gas Leakage Detection: a Deep Learning Framework on IR Video Data, Spatafora M.A.N., Allegra D., Giudice O., Stanco F., Battiato S., Proceedings - International Conference on Pattern Recognition, 2022, vol. 2022-August, pp. 636-642.
Cited by: 1
Undetected gas leakages may result in serious fire and explosion accidents with consequences like injuries among workers and financial losses. Automated leak detectors aimed to catch in time the gas emissions could reduce the incident risks. Several monitoring techniques have been developed over the years, among them the Optical Gas Imaging (OGI) is a widely-used method but it typically requires manual analysis (slow and error-prone). This paper introduces an automated gas leakage detection framework exploiting Infrared video data. A novel Recurrent Neural Network architecture was designed and trained on an ad-hoc collected large-scale dataset. Experimental results demonstrated the effectiveness of the proposed framework outperforming the state-of-the-art approaches with an average accuracy of 98%. The robustness of the technique was also validated in different scenarios and with different camera settings.
Conference Paper
Is synthetic voice detection research going into the right direction?, Borzi S., Giudice O., Stanco F., Allegra D., IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2022, vol. 2022-June, pp. 71-80.
Cited by: 2
Machine Learning, and in general Artificial Intelligence approaches, brought a great advance in each and every field of Computer Science increasing accuracy levels of predictors in any known problem. Indeed, this evolution enabled the construction of effective frameworks and solutions able to be used in investigative and forensics scenarios for detection of fakes and, in general, manipulations in multimedia contents. On the other hand, can we trust these systems? Is research activity going in the right direction? Are we just taking the low-hanging fruit without taking into account many real-case-in-the-wild situations? The purpose of this paper is to raise an alert to the research community in the specific context of synthetic voice detection, where data available for training is not big enough to give sufficient trust in the techniques available in the literature. To this aim, an exploratory investigation of the most common voice spoofing dataset was carried out and it was surprisingly easy to build simple classifiers without any Deep Learning techniques. Simple considerations on bitrate were sufficient to achieve an effective detection performance.
Conference Paper
Introducing AV1 Codec-Level Video Steganography, Catania L., Allegra D., Giudice O., Stanco F., Battiato S., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022, vol. 13231 LNCS, pp. 284-294.
Cited by: 0
Steganography is the ancient art of concealing messages into data. High research interest has grown over the last years, however, techniques in literature are only focused on standard and in some way legacy multimedia formats (e.g., H.264). Moreover, most video steganography techniques are based on concealing data into contents of each frame employing many strategies. In this paper, a codec-level video steganography technique is presented on the novel AV1: a royalty-free video compression format proposed by the Alliance for Open Media (AOM). The proposed method is based on the alteration of intra-prediction angles and, differently from other solutions, it works along the compression process, by allowing the encoder to reduce possible distortions caused by the messages to be hidden. The effectiveness of the technique was demonstrated by hiding up to 1024 characters into an highly compressed video of 40 s maintaining an average Peak Signal-to-Noise Ratio value of 37.53 dB.
Article
An ensembled anomaly detector for wafer fault detection, Furnari G., Vattiato F., Allegra D., Milotta F.L.M., Orofino A., Rizzo R., De Palo R.A., Stanco F., Sensors, 2021, vol. 21.
Cited by: 1
The production process of a wafer in the semiconductor industry consists of several phases such as a diffusion and associated defectivity test, parametric test, electrical wafer sort test, assembly and associated defectivity tests, final test, and burn-in. Among these, the fault detection phase is critical to maintain the low number and the impact of anomalies that eventually result in a yield loss. The understanding and discovery of the causes of yield detractors is a complex procedure of root-cause analysis. Many parameters are tracked for fault detection, including pressure, voltage, power, or valve status. In the majority of the cases, a fault is due to a combination of two or more parameters, whose values apparently stay within the designed and checked control limits. In this work, we propose an ensembled anomaly detector which combines together univariate and multivariate analyses of the fault detection tracked parameters. The ensemble is based on three proposed and compared balancing strategies. The experimental phase is conducted on two real datasets that have been gathered in the semiconductor industry and made publicly available. The experimental validation, also conducted to compare our proposal with other traditional anomaly detection techniques, is promising in detecting anomalies retaining high recall with a low number of false alarms.
Article
A robust document identification framework through f-bp fingerprint, Guarnera F., Giudice O., Allegra D., Stanco F., Battiato S., Livatino S., Matranga V., Salici A., Journal of Imaging, 2021, vol. 7.
Cited by: 2
The identification of printed materials is a critical and challenging issue for security purposes, especially when it comes to documents such as banknotes, tickets, or rare collectable cards: eligible targets for ad hoc forgery. State-of-the-art methods require expensive and specific industrial equipment, while a low-cost, fast, and reliable solution for document identification is increasingly needed in many contexts. This paper presents a method to generate a robust fingerprint, by the extraction of translucent patterns from paper sheets, and exploiting the peculiarities of binary pattern descriptors. A final descriptor is generated by employing a block-based solution followed by principal component analysis (PCA), to reduce the overall data to be processed. To validate the robustness of the proposed method, a novel dataset was created and recognition tests were performed under both ideal and noisy conditions.
Conference Paper
Exploiting Egocentric Vision on Shopping Cart for Out-Of-Stock Detection in Retail Environments, Allegra D., Litrico M., Spatafora M.A.N., Stanco F., Farinella G.M., Proceedings of the IEEE International Conference on Computer Vision, 2021, vol. 2021-October, pp. 1735-1740.
Cited by: 1
Continuous detection and efficient monitoring of Out-Of-Stock (OOS) of products in retail environments is a key factor to improve stores profits. Traditional methods require labour-intensive human work dedicated to checking for products to refill raising the requirement of automatic solutions to detect OOS. In this work, we focus on the problem of OOS detection from an egocentric perspective proposing a new weak annotation of the EgoCart dataset. We benchmark the considered challenge employing a deep learning approach for the detection of OOS areas. Specifically, we train a Convolutional Neural Network (CNN) to predict attention maps useful to find OOS in retail areas and hence suggest the retail employers where to intervene. We evaluate results with both objective measures and a subjective analysis provided by human which has reviewed the obtained OOS attention maps. The achieved performance demonstrates that the proposed pipeline is promising to help the refilling process in the retail domain.
Conference Paper
On the Exploitation of Temporal Redundancy to Improve Polyp Detection in Colonoscopy, Pappalardo G., Allegra D., Stanco F., Farinella G.M., 4th International Conference on Image Processing, Applications and Systems, IPAS 2020, 2020, pp. 58-63.
Cited by: 1
Colonoscopy is currently the most effective screening method to find precancerous colon polyps and plan their removal. Computer-Aided polyp detection can reduce polyp miss detection rates and help doctors find the most critical regions to pay attention to. The challenge in detecting polyps is due to the polyp's morphology and size, and these fall into false-negative. Indeed, polyps may exhibit high variability in shapes (e.g., depressed, flat, pedunculated, etc..). Moreover, the water injected from the endoscope results in artifacts which impede the detection, and the lubricating mucus causes light artifacts due its glossiness. To address this problem, we propose a mask-based attention mechanism to ensure that the employed detector focuses on particular regions of the image in order to reduce misdetection rate. Our contribution takes advantage of information on polyp's position over time within a video sequence. We provide such information through a binary mask which points out the last-known polyp's position. The proposed approach is validated on a dataset that has been labeled by colonoscopy experts. It contains about 200 videos and more than 500 different polyps with high variability in size and textures. Experimental results show that the proposed attention mechanism recover a smaller number of false negatives and achieves an Fl-score of 80.21%.
Conference Paper
Animated Gif Optimization by Adaptive Color Local Table Management, Giudice O., Allegra D., Guarnera F., Stanco F., Battiato S., Proceedings - International Conference on Image Processing, ICIP, 2020, vol. 2020-October, pp. 1206-1210.
Cited by: 0
After thirty years of the GIF file format, today is becoming more popular than ever: being a great way of communication for friends and communities on Instant Messengers and Social Networks. While being so popular, the original compression method to encode GIF images have not changed a bit. On the other hand popularity means that storage saving becomes an issue for hosting platforms. In this paper a parametric optimization technique for animated GIFs will be presented. The proposed technique is based on Local Color Table selection and color remapping in order to create optimized animated GIFs while preserving the original format. The technique achieves good results in terms of byte reduction with limited or no loss of perceived color quality. Tests carried out on 1000 GIF files demonstrate the effectiveness of the proposed optimization strategy.
Editorial
Pattern recognition and artificial intelligence techniques for cultural heritage, Fontanella F., Colace F., Molinara M., Scotto Di Freca A., Stanco F., Pattern Recognition Letters, 2020, vol. 138, pp. 23-29.
Cited by: 8
This paper is the editorial of the virtual special issue (VSI) “Pattern recognition and artificial intelligence techniques for cultural heritage”, of which the authors of this paper have been the guest editors. It aims to bring together the work of experts from the fields of pattern recognition and artificial intelligence and that of cultural heritage. This multidisciplinary subject covers a wide spectrum spanning from the study of the cultural heritage to the development of tools based on PR/AI techniques for cultural heritage analysis, reconstruction and understanding. The papers included in this special issue allowed us to highlight the advances on this subject from a wide-angle perspective, as well as to stimulate new theoretical and applied researches for better characterizing the state of the art in this domain.
Article
A method for similarity assessment between death masks and portraits through linear projection: The case of Vincenzo Bellini, Sequenzia G., Allegra D., Fatuzzo G., Milotta F.L.M., Stanco F., Oliveri S.M., Digital Applications in Archaeology and Cultural Heritage, 2020, vol. 17.
Cited by: 3
The aim of this study was to confirm the identities of numerous portraits attributed to the composer Vincenzo Bellini by using 3D-to-2D projection. This study also followed on from earlier research on three death masks of Bellini, the results of which had shown that the wax mask in Catania's Bellini museum best represented Bellini's face compared to the other two. This study used the aforementioned 3D wax death mask obtained through Reverse Engineering as a reference for a morphometric comparison with 14 other portraits. For each portrait, the linear 3D-to-2D transformation M was found which minimized the distance between the 2D landmarks in the picture and the projected landmarks on the 3D mask. This normalized the distances considering the scale of the portrait and the final dissimilarity score with the mask. In particular, the analytical results were able to identify two portraits which particularly resembled the 3D death mask providing future researchers with the chance to carry out historical-artistic evaluations. We were also able to develop a new tool – Image Mark Pro - to easily annotate 2D images by introducing landmark locations. Since it was so reliable for manually annotating landmarks, we decided to make it publicly available for future research.
Article
Conservation of the heinz and georges leichter dry plate collection, Egypt: Case study, Abdallah M., Ali M., Belal A., Stanco F., Mohareb F., Ali M., International Journal of Conservation Science, 2020, vol. 11, pp. 463-484.
Cited by: 1
The Heinz and Georges Leichter collection of gelatin dry plate negatives, located in Egypt, includes approximately 1000 negatives, 500 of which are gelatin dry plate negatives. The negatives were found to depict different subjects (i.e. archaeological sites, portraits, landscapes and others). Different formats and sizes were noted. Similar to other photographic materials, gelatin dry plate negatives consist of a layered structure which can be divided into three components: the primary support, glass; the binder layer, gelatin; and the final image material, silver grains. With regard to the state of preservation, the majority of the negatives were found to suffer from mechanical damage due to poor handling and improper housing, as well as chemical damage due to storage in unfavorable environmental conditions. This paper mainly aimed at studying the collection in terms of historical background, structure and state of preservation. It also evaluated several mirroring reduction/removal treatments for possible use with mirrored dry plate negatives prior to digitization for producing an enhanced copy of the original, which is a significant measure for safeguarding the context of these valuable records. Finally, it also aimed at preserving the collection for future generations through performing several conservation treatments. Several examination and analytical techniques were utilized to study five representative gelatin dry plates selected from the Leichter collection such as: visual inspection, USB digital microscope, stereomicroscope, and SEM-EDX. Fungal testing was also carried out to identify fungal growths.
Article
Challenges in automatic Munsell color profiling for cultural heritage, Milotta F.L.M., Furnari G., Quattrocchi C., Pasquale S., Allegra D., Gueli A.M., Stanco F., Tanasi D., Pattern Recognition Letters, 2020, vol. 131, pp. 135-141.
Cited by: 13
Color specification is the process of measuring the color of a sample in a given color space. We focused onto the Munsell color space as archaeologists are used to employ the so called Munsell Soil Color Charts (MSCCs) directly in the excavation sites. For these scholars and researchers, being enabled to perform Munsell color specification in an automatic way is crucial, as they spend a lot of time to subjectively specify colors in the Munsell system. We extended the dataset ARCA328, which was specifically thought for the automatic Munsell color specification issue, increasing the number of images from 328 to 1,488, and the number of samples from 56,160 to 315,333. Then, we conducted generalization-tests of color conversion for color specification, adopting a classification approach instead of a regression one. This choice was motivated by the fact that the set of all the possible HVC coordinates in the MSCCs is a discrete one. Hence, we decided to consider each chip in the MSCCs as a class to be learnt and recognized by the SVC. With these tests we highligthed the limits of automatic Munsell color specification without any reference-system or calibration phase. Finally, we gave insights for future works aimed to design automatic illuminant calibration phase and to investigate deep learning approaches, leveraging a synthetic images rendering procedure we also present in this work.
Article
I-PETER (Interactive platform to experience tours and education on the rocks): A virtual system for the understanding and dissemination of mineralogical-petrographic science, Sinitò D., Fugazzotto M., Stroscio A., Coccato A., Allegra D., Barone G., Mazzoleni P., Stanco F., Pattern Recognition Letters, 2020, vol. 131, pp. 85-90.
Cited by: 2
Nowadays mineralogical and petrographic sciences represent important resources for the understanding of natural and cultural heritage. Indeed, the implication in economic and social scenario, from the exploitation of geo-resources to the natural stone application in architecture, involves the whole society. In this context, scientific museums are called to enhance society awareness about the importance of minerals and rocks, while facilitating their understanding. It is well-known that the majority of the population is still left out from the museum fruition, usually because of problems of cultural accessibility. In order to find a solution, the Museum of Mineralogy, Petrography and Volcanology of the University of Catania implemented a new communication system based on the visitor's personal experience. The idea is to give to all users, regardless of their educational level, the possibility to learn by playing. The collaboration among geologists, conservators and computer scientists led to the implementation of a web application called I-PETER: Interactive Platform to Experience Tours and Education on the Rocks. The application, interacting with a database, offers to the public two different modes of exploring the museum's collections. The visitor can decide to observe the rocks or minerals from the sample exposed to the internal structure and then explore their external application on monuments, or he/she can choose to make a tour in the interactive map, focusing on a particular monument and from there make the virtual reverse path from the macro to the micro scale. Furthermore, thanks to the effort made to construct the knowledge base at the base of I-PETER web app, a labelled dataset of images of rocks and minerals can be easily released for future petrological investigations based on machine learning. Thanks to this pilot project, the museum's scientific knowledge can promote cultural tourism by making it more accessible to a wide public, as well as support scientific research on petrography and mineralogy.
Conference Paper
A digital approach for the study of roman signacula from syracuse, sicily, Tanasi D., Milotta F.L.M., Gradante I., Stanco F., Kaplan H., Italian Chapter Conference 2017 - Smart Tools and Apps in computer Graphics, STAG 2017, 2020, pp. 63-69.
Cited by: 0
In the last decade the epigraphists have grown a new interest in signacula, a class of artifacts for a long time neglected. This has brought numerous contributions devoted to the different regional contexts, along with reflections on methodological questions, not to mention the momentum towards the digitizing of a corpus which counts at least 3,500 pieces, confirming the great potential of these artifacts in providing information related not only to the economy and to the administration of the “res”, both in public and private sphere, but also about the profile of the signacula holders. In this scenario, a specific research question has been inspired by the Sicilian seals - about 60 signacula and a dozen impressions left by seals on mortar in burial contexts: it is possible to identify unequivocally a signaculum through its impression? Given for granted that the use of 3D documentation will bring along effective results in terms of improved readability of signacula and seals, the aim of this contribute is to establish a protocol for a semi-automatic matching between 3D models of seals and 3D models of impressions. As part of a preliminary scanning campaign of Late Roman impressions on mortars and metal seals from the catacombs of Syracuse, two bronze metal seals were digitized with a NextEngine 3D triangulation laser scanner and subsequently 3D printed with liquid resin with a Formlabs Form 2 SLA high resolution printer. The casts obtained, were experimentally used to create a set of impressions on mortar using different degrees and angles of pressure, in order to create similar but still different stamps. During the next step, the impressions were 3D scanned and used as ground truth for the outlined semi-automatic procedure of matching with the seals. In MeshLab environment, the 3d models of seals and impressions were manually aligned and then the distance between two sets of 3D points was measured using the filter Hausdorff distance in order to validate a matching. This successful exercise could open the way to the proposal of creating a virtual edition of signacula with 3D models metadata. Furthermore, a research agenda may include the design of a machine learning algorithm for matching of 3D meshes.
Conference Paper
A New Study on Wood Fibers Textures: Documents Authentication Through LBP Fingerprint, Guarnera F., Allegra D., Giudice O., Stanco F., Battiato S., Proceedings - International Conference on Image Processing, ICIP, 2019, vol. 2019-September, pp. 4594-4598.
Cited by: 8
The authentication of printed material based on textures is a critical and challenging problem for many security agencies in many contexts: valuable documents, banknotes, tickets or rare collectible cards are often targets for forgery. This motivates the study of low-cost, fast and reliable approaches for documents authenticity analysis. In this paper, we present a new approach based on the extraction of translucent patterns from paper sheet by means of a specific-built framework. A fingerprint is obtained by computing a Local Binary Pattern descriptor on the digital image. To validate the robustness of the proposed method for authentication analysis, we introduce a novel dataset and perform retrieval tests under both, ideal and noisy conditions. Experimental results prove the validity of the proposed strategy.
Conference Paper
A New Framework for Studying Tubes Rearrangement Strategies in Surveillance Video Synopsis, Pappalardo G., Allegra D., Stanco F., Battiato S., Proceedings - International Conference on Image Processing, ICIP, 2019, vol. 2019-September, pp. 664-668.
Cited by: 6
The manual review of raw surveillance video is a time consuming task which can be optimized by using a Video Synopsis (VS) algorithm. The aim of such approaches is to condense a long video into shorter one to allow a quicker review of surveillance data. However, VS is a complex problem. A typical object-based VS algorithm requires three main modules to perform the following tasks: object detection and tracking, tubes rearrangement, condensed video generation. Although the aforementioned three steps are equally critical, we realized that the core of Video Synopsis lies in the tubes rearrangement. This led us to propose an original approach to tackle the problem of tubes rearrangement. To this aim, we first introduce a new toolbox to generate a proper testing dataset, which allows to bypass the lack of public databases including proper annotated videos for testing synopsis approaches. Additionally, we propose an improvement of a tubes arrangement algorithm based on graph colouring and we prove its validity on our generated dataset. For a proper comparison, we show that our algorithm also outperforms the original one on UA-DETRAC public dataset.
Article
Breast Shape Analysis with Curvature Estimates and Principal Component Analysis for Cosmetic and Reconstructive Breast Surgery, Catanuto G., Taher W., Rocco N., Catalano F., Allegra D., Milotta F.L.M., Stanco F., Gallo G., Nava M.B., Aesthetic Surgery Journal, 2019, vol. 39, pp. 164-173.
Cited by: 3
Background: Breast shape is defined utilizing mainly qualitative assessment (full, flat, ptotic) or estimates, such as volume or distances between reference points, that cannot describe it reliably. Objectives: The authors quantitatively described breast shape with two parameters derived from a statistical methodology denominated by principal component analysis (PCA). Methods: The authors created a heterogeneous dataset of breast shapes acquired with a commercial infrared 3-dimensional scanner on which PCA was performed. The authors plotted on a Cartesian plane the two highest values of PCA for each breast (principal components 1 and 2). Testing of the methodology on a preoperative and posttreatment surgical case and test-retest was performed by two operators. Results: The first two principal components derived from PCA characterize the shape of the breast included in the dataset. The test-retest demonstrated that different operators obtain very similar values of PCA. The system is also able to identify major changes in the preoperative and posttreatment stages of a two-stage reconstruction. Even minor changes were correctly detected by the system. Conclusions: This methodology can reliably describe the shape of a breast. An expert operator and a newly trained operator can reach similar results in a test/re-testing validation. Once developed and after further validation, this methodology could be employed as a good tool for outcome evaluation, auditing, and benchmarking.
Conference Paper
Hyperspectral image classification via convolutional neural network based on dilation layers, Devaram R.R., Allegra D., Gallo G., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11751 LNCS, pp. 378-387.
Cited by: 6
Classification of hyperspectral images is one of the main problem in the research field of Remote Sensing. With the advantage of spectral and spatial information, it is possible to distinguish effectively different materials and terrains. In the last decade, the intensive employing of Convolutional Neural Networks (CNN) for classification and segmentation task led high quality results in the field of Hyperspectral Imaging. In this paper, we propose a novel CNN architecture for HSI pixel-wise classification. In order to improve state-of-art results, the proposed approach focuses on the use of Dilated Convolution. Also, to face dataset imbalance problem we adopt an oversampling strategy which increases the samples in minority classes. To prove the validity of the proposed framework, we tested it on five different HSI datasets and compared the performance with the most successful previous works. Achieved performances prove that our approach is competitive with the state-of-art and exhibits the best results on all the employed datasets.
Conference Paper
Learning to rank food images, Allegra D., Erba D., Farinella G.M., Grazioso G., Maci P.D., Stanco F., Tomaselli V., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11752 LNCS, pp. 629-639.
Cited by: 1
In the last decade food understanding has become a very attractive topic. This has implied the growing demand of Computer Vision algorithms for automatic diet assessment to treat or prevent food related diseases. However, the intrinsic variability of food, makes the research in this field incredibly challenging. Although many papers about classification or recognition of food images have been published in recent years, the literature lacks of works which address volume and calories estimation problem. Since an ideal food understanding engine should be able to provide information about nutritional values, the knowledge of the volume is essential. Differently from the state-of-art works, in this paper we address the problem of volume estimation through Learning to Rank algorithms. Our idea is to work with a predefined set of possible portion size and exploit a ranking approach based on Support Vector Machine (SVM) to sort food images according to the volume. At the best of our knowledge, this is the first work where food volume analysis is treated as a raking problem. To validate the proposed methodology we introduce a new dataset of 99 food images related to 11 food plates. Each food image belongs to one over three possible portion size (i.e., small, medium, large). Then, we provide a baseline experiment to assess the problem of learning to rank food images by using three different image descriptors based on Bag of Visual Words, GoogleNet and MobileNet. Experimental results, confirm that the exploited paradigm obtain good performances and that a ranking function for food volume analysis can be successfully learnt.
Conference Paper
Augmented Reality for the Valorization and Communication of Ruined Architecture, Garozzo R., Pasqualino G., Allegra D., Santagati C., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11808 LNCS, pp. 170-178.
Cited by: 0
This paper is focused on the valorization and the communication about the Mother church of Santa Maria delle Grazie in the Ancient Misterbianco (Catania), one of the rare surviving vestiges of the eruption of Mount Etna in 1669 and the earthquake in Val di Noto in 1693. The project, starting from a 3D digital surveys carried out through reality-based techniques, uses an Augmented Reality approach to propose a virtual re-positioning of some significant elements of the church, removed during the eruption. This study required a deep architectural study and an archival documents research to exactly identify the original location of the re-positioned artworks. Then, a 3D reconstruction carried out to get accurate 3D models of them and Augmented Reality application allows the visitors to experience the current church environment enriched with these original artefacts, in order to achieve a more powerful learning/visiting experience.
Article
Automatic color classification via Munsell system for archaeology, Milotta F.L.M., Tanasi D., Stanco F., Pasquale S., Stella G., Gueli A.M., Color Research and Application, 2018, vol. 43, pp. 929-938.
Cited by: 11
Munsell soil charts are commonly used in archaeology to identify colors of soils and artifacts during excavations. In situ, the procedure is done by visual means and in a very subjective way, resulting in a time consuming and error-prone approach. To overcome these limitations, an original application has been developed: the automatic recognition of color for archaeology (ARCA). ARCA is a framework thought to be a valuable asset for archaeologists since it may be objective, deterministic, and fast. In this framework, it is possible to convert RGB data to HVC color space. Users may import images in ARCA through a proper desktop application, which also allows operators to sample RGB manually data. Then, HVC notation is automatically estimated and provided to operators within an automatically generated filled report. ARCA moves from Munsell charts, but it has the advantage of providing an objective and affordable color specification system. In this study, we present the results related to data acquired in a controlled lightning environment with a color assessment cabinet on Munsell soil color charts to try to improve the lightness estimation. We focused on two color space conversions: RGB to HVC, and RGB to L*a*b* of CIELAB color space. Color coordinates are obtained through colorimetric measurements. We developed a method with three main phases, and we computed transformation coefficients from observed and ground truth data. The color accuracy of our method is presented in terms of Godlove distance and through CIEDE1976, CIEDE2000, ΔL*, Δa*, and Δb* CIE metrics.
Article
Munsell Color Specification using ARCA (Automatic Recognition of Color for Archaeology), Milotta F.L.M., Stanco F., Tanasi D., Gueli A.M., Journal on Computing and Cultural Heritage, 2018, vol. 11.
Cited by: 10
Munsell Soil Charts are a very common tool used by archaeologists for the color specification task. Charts are usually employed directly on cultural heritage sites to identify color of soils and collected artifacts. However, charts are designed to be used specifying the color through subjective perception of users, by visual mean, in a time-consuming and error-prone procedure. It is likely that two users may estimate different Munsell notations for the same specimen, as colors are not perceived uniformly by different people. Hence, estimation process should be repeated several times and by more than a single expert user to be considered reliable. In this work, we employ our framework, Automatic Recognition of Color for Archaeology (ARCA), specifically designed to provide a method for objective, deterministic, fast, and automatic Munsell estimation. ARCA is a valuable asset for archaeologists as it provides the definition of a smooth pipeline for an affordable Munsell notation estimation: image acquisition of specimens with general purpose digital cameras in an uncontrolled environment, manual sampling of specimen images in the ARCA desktop application, automatic Munsell color specification, and report generation. We further assess our method with improved color tolerance validations and evaluations, introducing a comparison between ΔE00, ΔE76, ΔL∗, Δa∗, and Δb∗ differences. One of the main contributions of this article is the extension of our former dataset ARCA108. We gathered two additional sets of images obtaining a new dataset consisting of pictures of Munsell Soil Charts Editions 2000 and 2009 plus images from a real test case with 16 pottery shards. The new dataset counts 56,160 samples and 328 images, so it has been called ARCA328. Experimental results are reported to investigate which could be the best configuration to be used in the acquisition phase.
Conference Paper
ARCA 2.0: Automatic Recognition of Color for Archaeology through a Web-Application, Milotta F.L.M., Quattrocchi C., Stanco F., Tanasi D., Pasquale S., Gueli A.M., 2018 IEEE International Conference on Metrology for Archaeology and Cultural Heritage, MetroArchaeo 2018 - Proceedings, 2018, pp. 466-470.
Cited by: 5
ARCA stands for Automatic Recognition of Color for Archaeology. Color specification is a common and critical issue for archaeologists, motivated by the need to identify and catalogue color names. For these purposes, Munsell Soil Color Charts (MSCCs) are widely employed. However, archaeologists are used to perform color specification by visual means, through a procedure that was proved to be time consuming, subjective and error-prone. In its first version, ARCA has been presented as the products of our project to realize an application that could be objective and easy to use directly in the excavation sites. In this paper, we present ARCA 2.0: A totally reshaped method for color specification relying onto empiric transformations specifically tuned for cultural heritage color specification. As in the previous version, ARCA 2.0 is made for RGB to HVC (Munsell) color conversion. We validate and assess the newer method, releasing a set of coefficients that can be used by other researchers for color specification tasks. We also present a demo of the web application based onto experimental results achieved during this research.
Article
Evaluation of Levenberg-Marquardt neural networks and stacked autoencoders clustering for skin lesion analysis, screening and follow-up, Rundo F., Conoci S., Banna G.L., Ortis A., Stanco F., Battiato S., IET Computer Vision, 2018, vol. 12, pp. 957-962.
Cited by: 28
Traditional methods for early detection of melanoma rely on the visual analysis of the skin lesions performed by a dermatologist. The analysis is based on the so-called ABCDE (Asymmetry, Border irregularity, Colour variegation, Diameter, Evolution) criteria, although confirmation is obtained through biopsy performed by a pathologist. The proposed method exploits an automatic pipeline based on morphological analysis and evaluation of skin lesion dermoscopy images. Preliminary segmentation and pre-processing of dermoscopy image by SC-cellular neural networks is performed, in order to obtain ad-hoc grey-level skin lesion image that is further exploited to extract analytic innovative hand-crafted image features for oncological risks assessment. In the end, a pre-trained Levenberg-Marquardt neural network is used to perform ad-hoc clustering of such features in order to achieve an efficient nevus discrimination (benign against melanoma), as well as a numerical array to be used for follow-up rate definition and assessment. Moreover, the authors further evaluated a combination of stacked autoencoders in lieu of the Levenberg-Marquardt neural network for the clustering step.
Conference Paper
Experiences in using the pepper robotic platform for museum assistance applications, Allegra D., Alessandro F., Santoro C., Stanco F., Proceedings - International Conference on Image Processing, ICIP, 2018, pp. 1033-1037.
Cited by: 6
This paper presents the software architecture of a robotic museum guide application called Cuma. It is intended to run upon the Pepper robotic platform and has the objective of guiding visitors of a museum accompanying them in the tour, explaining museum works, and interacting with them in order to gather feedback. Cuma has been partially implemented and preliminarily tested. The results reported in the paper, highlight that even if Pepper, from the structural point of view, seems particularly suited for this kind of application, the provided software platform presents some important limitations thus requiring the integration of external tools and algorithms.
Conference Paper
A Fast Palette Reordering Technique Based on GPU-Optimized Genetic Algorithms, Giudice O., Allegra D., Stanco F., Grasso G., Battiato S., Proceedings - International Conference on Image Processing, ICIP, 2018, pp. 1138-1142.
Cited by: 7
Color re-indexing is one of main approaches for improving the loss-less compression of color indexed images. Zero-order entropy reduction of indexes matrix is the key to obtain high compression ratio. However, obtaining the optimal re-indexed palette is a challenging problem that cannot be solved by brute-force approaches. In this paper we propose a novel re-indexing approach where the Travelling Salesman Problem is solved through Ant Colony Optimization. Our method is proved to achieve high quality results by outperforming state-of-art ones in term of compression gain. Additionally, we exploit clustering and GPU computing to make our solution extremely fast.
Editorial
Foreword to the Special Section on Smart Tools and Applications in Computer Graphics 2017, Giachetti A., Pingi P., Stanco F., Computers and Graphics (Pergamon), 2018, vol. 74, pp. A6-A7.
Cited by: 0
Conference Paper
Randomized G-Computation Models in Healthcare Systems, Spera E., Gallo G., Allegra D., Stanco F., Maugeri A., Quattrocchi A., Barchitta M., Agodi A., Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2018, vol. 2018-June, pp. 77-81.
Cited by: 1
Healthcare system quality improvements depend both on the availability of innovative technologies and on proper investments to transfer experimental policies into daily practices that could be easily adopted in all hospitals. Unfortunately, funds are generally not enough to cover all the addressable issues and the policy makers are faced with the difficult problem to decide where to allocate the money to produce the most relevant positive outcomes. To support this decision process, data gathering, and analysis play a key role. In this contribution we propose a simplified pipeline that starting from observational data to achieve statistical conclusions as valid as in designed randomized studies. After detailing the proposed analytic method, its soundness is proved using an important case study: the problem of the reduction of Healthcare-Associated Infections, and especially those acquired in Intensive Care Units. In particular, we show how to estimate the preventable proportion of Intubation-Associated Pneumonia in ICUs. In our study, using G-Computation based approach, we found out that the preventable proportion for IAP is of 44%. Interestingly, when bundle compliance is added in the statistical model, the preventable proportion for IAP is of 40%.
Conference Paper
A multi-task learning approach for meal assessment, Lu Y., Allegra D., Anthimopoulos M., Stanco F., Farinella G., Mougiakakou S., ACM International Conference Proceeding Series, 2018, pp. 46-52.
Cited by: 28
Key role in the prevention of diet-related chronic diseases plays the balanced nutrition together with a proper diet. The conventional dietary assessment methods are time-consuming, expensive and prone to errors. New technology-based methods that provide reliable and convenient dietary assessment, have emerged during the last decade. The advances in the field of computer vision permitted the use of meal image to assess the nutrient content usually through three steps: food segmentation, recognition and volume estimation. In this paper, we propose a use one RGB meal image as input to a multi-task learning based Convolutional Neural Network (CNN). The proposed approach achieved outstanding performance, while a comparison with state-of-the-art methods indicated that the proposed approach exhibits clear advantage in accuracy, along with a massive reduction of processing time.
Article
Restoration of silver gelatin prints in the digital era: An innovative approach, Yosri M., Ali M., Stanco F., Talaat K., International Journal of Conservation Science, 2018, vol. 9, pp. 375-388.
Cited by: 2
One of the most common physical damage in silver gelatin prints is losses which occurs due to many deterioration factors (i.e. rodent attack, improper handling, fire, etc.). Conventionally, conservators compensated for the losses by making paper infills. While this method improves the physical structure of the treated print, it creates an unacceptable appearance due to the large contrast between the tone of the original photograph and the blank paper. Manual retouching of the missing part does not provide a better solution either, since it is achieved using a different medium (i.e. watercolors, ink washes, conté crayons, pastels, and graphite). Many conservators are now aware of the advantages of digital restoration in treating old photographs. Hence, the importance of this study, which focuses mainly on modifying conventional methods used to treat losses by combining it with a digital restoration technique. The concept of this idea is solely based on the authors' vision. Accordingly, the main aim of this paper is to evaluate the efficiency of the proposed novel technique. Experiments were carried out on two old photographs of no significant value. Both photographs suffered from losses, particularly around the edges. Missing parts were digitally restored using Adobe Photoshop Software. Restored image data was then printed on Japanese paper using two types of printers: inkjet and laser. Samples or each printing process was exposed to artificial aging at a temperature of 80° and 65% relative humidity for a period of 120 hours to study the long-term efficacy of the proposed technique; as well as the effects it has on silver gelatin prints. Several examination and analysis methods were carried out for technique evaluation including: visual inspection, scanning electron microscope equipped with an EDX unit, attenuated total Reflectance Fourier transform Infrared (ATRFTIR), colorimetric measurements, pH value measurement, and the Oddy test. Based on obtained results, laser printing is much more stable compared to inkjet printing; and therefore, it is considered the best option for this technique. All in all, one can conclude that the proposed technique is a very promising technique which can be efficiently used to restore losses in damaged photographic prints with slight effects on the original photograph.
Conference Paper
A Multimedia Database for Automatic Meal Assessment Systems, Allegra D., Anthimopoulos M., Dehais J., Lu Y., Stanco F., Farinella G.M., Mougiakakou S., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10590 LNCS, pp. 471-478.
Cited by: 16
A healthy diet is crucial for maintaining overall health and for controlling food-related chronic diseases, like diabetes and obesity. Proper diet management however, relies on the rather challenging task of food intake assessment and monitoring. To facilitate this procedure, several systems have been recently proposed for automatic meal assessment on mobile devices using computer vision methods. The development and validation of these systems requires large amounts of data and although some public datasets already exist, they don’t cover the entire spectrum of inputs and/or uses. In this paper, we introduce a database, which contains RGB images of meals together with the corresponding depth maps, 3D models, segmentation and recognition maps, weights and volumes. We also present a number of experiments on the new database to provide baselines performances in the context of food segmentation, depth and volume estimation.
Conference Paper
Bio-Inspired Feed-Forward System for Skin Lesion Analysis, Screening and Follow-Up, Rundo F., Conoci S., Banna G.L., Stanco F., Battiato S., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10485 LNCS, pp. 399-409.
Cited by: 7
Traditional methods for early detection of melanoma rely upon a dermatologist who visually analyzes skin lesion using the so called ABCDE (Asymmetry, Border irregularity, Color variegation, Diameter, Evolution) criteria even though conclusive confirmation is obtained through biopsy performed by pathologist. The proposed method shows a bio-inspired feed-forward automatic pipeline based on morphological analysis and evaluation of skin lesion dermoscopy image. Preliminary segmentation and pre-processing of dermoscopy image by SC-Cellular Neural Networks is performed in order to get ad-hoc gray-level skin lesion image in which we compute analytic innovative hand-crafted image features for oncological risks assessment. At the end, pre-trained Levenberg-Marquardt Neural Network is used to perform ad-hoc clustering of such hand-crafted image features in order to get an efficient nevus discrimination (benign against melanoma) as well as a numerical array to be used for follow-up rate definition and assessment.
Editorial
Preface, Battiato S., Gallo G., Schettini R., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10484 LNCS, pp. V-VII.
Cited by: 2
Conference Paper
Organizing videos streams for clustering and estimation of popular scenes, Battiato S., Farinella G.M., Milotta F.L.M., Ortis A., Stanco F., D’Amico V., Addesso L., Torrisi G., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10484 LNCS, pp. 51-61.
Cited by: 3
The huge diffusion of mobile devices with embedded cameras has opened new challenges in the context of the automatic understanding of video streams acquired by multiple users during events, such as sport matches, expos, concerts. Among the other goals there is the interpretation of which visual contents are the most relevant and popular (i.e., where users look). The popularity of a visual content is an important cue exploitable in several fields that include the estimation of the mood of the crowds attending to an event, the estimation of the interest of parts of a cultural heritage, etc. In live social events people capture and share videos which are related to the event. The popularity of a visual content can be obtained through the “visual consensus” among multiple video streams acquired by the different users devices. In this paper we address the problem of detecting and summarizing the “popular scenes” captured by users with a mobile camera during events. For this purpose, we have developed a framework called RECfusion in which the key popular scenes of multiple streams are identified over time. The proposed system is able to generate a video which captures the interests of the crowd starting from a set of the videos by considering scene content popularity. The frames composing the final popular video are automatically selected from the different video streams by considering the scene recorded by the highest number of users’ devices (i.e., the most popular scene).
Conference Paper
Description of Breast Morphology Through Bag of Normals Representation, Allegra D., Milotta F.L.M., Sinitò D., Stanco F., Gallo G., Taher W., Catanuto G., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10485 LNCS, pp. 511-521.
Cited by: 2
In this work we focus on digital shape analysis of breast models to assist breast surgeon for medical and surgical purposes. A clinical procedure for female breast digital scan is proposed. After a manual ROI definition through cropping, the meshes are automatically processed. The breasts are represented exploiting “bag of normals” representation, resulting in a 64-d descriptor. PCA is computed and the obtained first 2 principal components are used to plot the breasts shape into a 2D space. We show how the breasts subject to a surgery change their representation in this space and provide a cue about the error in this estimation. We believe that the proposed procedure represents a valid solution to evaluate the results of surgeries, since one of the most important goal of the specialists is to symmetrically reconstruct breasts and an objective tool to measure the result is currently missing.
Conference Paper
ARCA (Automatic Recognition of Color for Archaeology): A Desktop Application for Munsell Estimation, Milotta F., Stanco F., Tanasi D., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10485 LNCS, pp. 661-671.
Cited by: 7
Archaeologists are used to employing the Munsell Soil Charts on cultural heritage sites to identify colors of soils and retrieved artifacts. The standard practice of Munsell estimation exploits the Soil Charts by visual means. This procedure is error prone, time consuming and very subjective. To obtain an accurate estimation the process should be repeated multiple times and possibly by other users, since colors might not be perceived uniformly by different people. Hence, a method for objective and automatic Munsell estimation would be a valuable asset to the field of archaeology. In this work we present ARCA: Automatic Recognition of Color for Archaeology, a desktop application for Munsell estimation. The following pipeline for Munsell estimation aimed towards archaeologists has been proposed: image acquisition of specimens, manual sampling of the image in the ARCA desktop application, automatic Munsell estimation of the sampled points and creation of a sampling report. A dataset, called ARCA108, consisting of 22, 848 samples has been gathered, in an unconstrained environment, and evaluated with respect to the Munsell Soil Charts. Experimental results are reported to define the best configuration that should be used in the acquisition phase. Color tolerance values of the proposed framework are also reported.
Editorial
Preface, Battiato S., Gallo G., Schettini R., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, vol. 10485 LNCS, pp. V-VII.
Cited by: 0
Editorial
Special Section Guest Editorial:Image Processing for Cultural Heritage, Chetouani A., Erdmann R., Picard D., Stanco F., Journal of Electronic Imaging, 2017, vol. 26.
Cited by: 2
Article
Virtual anastylosis of Greek sculpture as museum policy for public outreach and cognitive accessibility, Stanco F., Tanasi D., Allegra D., Milotta F.L.M., Lamagna G., Monterosso G., Journal of Electronic Imaging, 2017, vol. 26.
Cited by: 20
This paper deals with a virtual anastylosis of a Greek Archaic statue from ancient Sicily and the development of a public outreach protocol for those with visual impairment or cognitive disabilities through the application of three-dimensional (3-D) printing and haptic technology. The case study consists of the marble head from Leontinoi in southeastern Sicily, acquired in the 18th century and later kept in the collection of the Museum of Castello Ursino in Catania, and a marble torso, retrieved in 1904 and since then displayed in the Archaeological Museum of Siracusa. Due to similar stylistic features, the two pieces can be dated to the end of the sixth century BC. Their association has been an open problem, largely debated by scholars, who have based their hypotheses on comparisons between pictures, but the reassembly of the two artifacts was never attempted. As a result the importance of such an artifact, which could be the only intact Archaic statue of a kouros ever found in Greek Sicily, has not fully been grasped by the public. Consequently, the curatorial dissemination of the knowledge related with such artifacts is purely based on photographic material. As a response to this scenario, the two objects have been 3-D scanned and virtually reassembled. The result has been shared digitally with the public via a web platformand, in order to include increased accessibility for the public with physical or cognitive disabilities, copies of the reassembled statue have been 3-D printed and an interactive test with the 3-Dmodel has been carried out with a haptic device.
Article
Integrated three-dimensional models for noninvasive monitoring and valorization of the Morgantina silver treasure (Sicily), Alberghina M.F., Alberghina F., Allegra D., Di Paola F., Maniscalco L., Milazzo G., Milotta F.L.M., Pellegrino L., Schiavone S., Stanco F., Journal of Electronic Imaging, 2017, vol. 26.
Cited by: 4
The Morgantina silver treasure belonging to the Archaeological Museum of Aidone (Sicily) was involved in a three-dimensional (3-D) survey and diagnostics campaign for monitoring the collection over time in anticipation of their temporary transfer to the Metropolitan Museum of Art in New York for a period of 4 years. Using a multidisciplinary approach, a scientific and methodological protocol based on noninvasive techniques to achieve a complete and integrated knowledge of the precious items and their conservation state, as well as to increase their valorization, has been developed. All acquired data, i.e., 3-D models, ultraviolet fluorescence, x-ray images, and chemical information, will be made available, in an integrated way, within a web-oriented platform, which will present an in-progress tool to deepen existing archaeological knowledge and production technologies and to obtain referenced information of the conservation state before and after moving of the collection from its exposure site.
Article
Retrieval and classification of food images, Farinella G.M., Allegra D., Moltisanti M., Stanco F., Battiato S., Computers in Biology and Medicine, 2016, vol. 77, pp. 23-39.
Cited by: 81
Automatic food understanding from images is an interesting challenge with applications in different domains. In particular, food intake monitoring is becoming more and more important because of the key role that it plays in health and market economies. In this paper, we address the study of food image processing from the perspective of Computer Vision. As first contribution we present a survey of the studies in the context of food image processing from the early attempts to the current state-of-the-art methods. Since retrieval and classification engines able to work on food images are required to build automatic systems for diet monitoring (e.g., to be embedded in wearable cameras), we focus our attention on the aspect of the representation of the food images because it plays a fundamental role in the understanding engines. The food retrieval and classification is a challenging task since the food presents high variableness and an intrinsic deformability. To properly study the peculiarities of different image representations we propose the UNICT-FD1200 dataset. It was composed of 4754 food images of 1200 distinct dishes acquired during real meals. Each food plate is acquired multiple times and the overall dataset presents both geometric and photometric variabilities. The images of the dataset have been manually labeled considering 8 categories: Appetizer, Main Course, Second Course, Single Course, Side Dish, Dessert, Breakfast, Fruit. We have performed tests employing different representations of the state-of-the-art to assess the related performances on the UNICT-FD1200 dataset. Finally, we propose a new representation based on the perceptual concept of Anti-Textons which is able to encode spatial information between Textons outperforming other representations in the context of food retrieval and Classification.
Article
Tracking error in digitized analog video: Automatic detection and correction, Stanco F., Allegra D., Milotta F.L.M., Multimedia Tools and Applications, 2016, vol. 75, pp. 3733-3746.
Cited by: 5
In the last half century the most used video storage devices have been the magnetic tapes, where the information are stored in analog format based on the electromagnetism principles. When the digital technique has become the most used, it was necessary to convert analog information in digital format in order to preserve these data. Unfortunately, analog videos may be affected by drops that produce some visual defect which could be acquired during the digitization process. Despite there are many hardware to perform the digitization, just few implement the automatic correction of these defects. In some cases, drop removal is possible through the analog device. However, when a damaged already-converted video is owned, a correction based on image processing technique is the unique way to enhance the videos. In this paper, the drop, also known as “Tracking Error” or “Mistracking,” is analyzed. We propose an algorithm to detect the drops’ visual artifacts in the converted videos, as well as a digital restoration method.
Article
X-ray computed tomography for virtually unrolling damaged papyri, Allegra D., Ciliberto E., Ciliberto P., Petrillo G., Stanco F., Trombatore C., Applied Physics A: Materials Science and Processing, 2016, vol. 122.
Cited by: 7
The regular format for ancient works of literature was the papyrus roll. Recently many efforts to perform virtual restoration of this archeological artifact have been done. In fact the case of ancient rolled papyrus is very intriguing. Old papyruses are the substrates of very important historical information, probably being the use of papyrus dated to the Pre-Dynastic Period. Papyrus degradation is often very hard so that physical unrolling is sometime absolutely impossible. In this paper, authors describe their effort in setting a new virtual restoration methodology based on software manipulation of X-ray tomographic images. A realistic model, obtained by painting a hieroglyph inscription of Thutmosis III on a papyrus substrate made by the original method described by Plinius the Elder and by pigments and binders compatible with the Egyptian use (ochers with natural glue), was made for the X-ray investigation. A GE Optima 660 64 slice was used to obtain a stack of tomographic slices of the rolled model. Each slice appears as spiral. The intensity variations along the cross-sectional result from ink on the papyrus. The files were elaborated with original software, written by the use of MATLAB high-level language, and the final result was quite similar to the radiography of the physically unrolled sheet.
Conference Paper
Low cost handheld 3D scanning for architectural elements acquisition, Allegra D., Gallo G., Inzerillo L., Lombardo M., Milotta F.L.M., Santagati C., Stanco F., Italian Chapter Conference 2016 - Smart Tools and Apps in Computer Graphics, STAG 2016, 2016, pp. 127-131.
Cited by: 18
3D scanning has gone a long way since its first appearance in cultural heritage digitization and modeling. In the recent years some new low cost, fast, accurate emerging technologies are flooding the market. Envisioning the massive use of these cheap and easy to use devices in the next years, it is crucial to explore the possible fields of application and to test their effectiveness in terms of easiness of 3D data collection, processing, mesh resolution and metric accuracy against the size and features of the objects. In this study we focus the attention on one emerging technology, the Structure Sensor device, in order to verify a 3D pipeline acquisition on an architectural element and its details. The methodological approach is thought to define a pipeline of 3D acquisition exploiting low cost and open source technologies and foresees the assessment of this procedure in comparison with data obtained by a Time of Flight device.
Conference Paper
3D digital imaging for knowledge dissemination of Greek archaic statuary, Stanco F., Tanasi D., Allegra D., Milotta F.L.M., Italian Chapter Conference 2016 - Smart Tools and Apps in Computer Graphics, STAG 2016, 2016, pp. 133-141.
Cited by: 2
This paper aims, using a research exercise, to verify the association between two Greek sculptures collected at different times: the head of a boy collected in the Chalcidian colony of Leontinoi in southeastern Sicily, acquired in the 18th century and later kept in the collection of the Museum of Castello Ursino in Catania, and a torso, retrieved in 1904 and since then displayed in the Archaeological Museum of Sicily. The two pieces share similar stylistic features and represent the most significant example of Greek sculpture in Sicily at the end of the 6th century BC. Their association is an open problem still debated by scholars, who have based their studies on comparisons between pictures as a reassembly of two artefacts was never attempted. This critical issue has conditioned curators of the two museums, who could not develop a proper communication policy for the two objects, resulting in a limited cognitive accessibility for the public. By means of 3D scanning techniques, this contribution showcases how virtual restoration can not only improve interpretations of the scholars, but also boost the communication plans of museums, giving back to the public via a web platform a masterpiece of Greek sculpture known just by specialists.
Conference Paper
RECfusion: Automatic scene clustering and tracking in videos from multiple sources, Milotta F., Battiato S., Stanco F., D'amico V., Torrisi G., Addesso L., IS and T International Symposium on Electronic Imaging Science and Technology, 2016.
Cited by: 3
RECfusion is a framework devoted to the automatic processing of video data from many devices, as smartphones, tablets, webcams, surveillance cameras, etc., where all devices are thought to be connected into a 4G LTE network. Exploiting this mobile ultra-broadband connection the communication paradigm between users in the social media context can be augmented: in events like concerts, feasts, expos and so on, users become either producers than fruitors of video data. RECfusion analyzes video streams from several devices and infers semantics performing scene understanding. Key scenes are identified with relation on each video stream and all the other ones; then the system generates a video rendered from a mixage of the selected video streams. In ref. [1] a system based upon visual content popularity has been already implemented in RECfusion. In this work we propose an extension for RECfusion: a novel automatic video cluster tracking algorithm able to identify the different scenes in the gathered video streams selecting for each of them the best recording device.
Conference Paper
Breast shape parametrization through planar projections, Gallo G., Allegra D., Atani Y.G., Milotta F.L.M., Stanco F., Catanuto G., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, vol. 10016 LNCS, pp. 135-146.
Cited by: 5
In the last years, 3D scanning has replaced the low tech approach to acquire direct anthropometric measurements. These new methodologies provide a detailed digital model of the body and allow analysis of more complex information like volume, shape, curvature, and so on. The possibility to acquire the shape of soft tissues, such as the female human breast, has attracted the interest breast surgery specialists. The main aim of this work is to propose an innovative strategy to automatically analyze 3D breast shape in order to describe them within a quantitative well defined framework. In particular we propose a scanning procedure for a proper acquisition of breast surfaces by using the handheld scanner Structure Sensor, as well as a framework to process 3D digital data to extract the shape information. The proposed method consists in two main parts: firstly, the acquired digital 3D surfaces are projected in a 2D space and a set of 17 geometrical landmarks are extracted; then by exploiting Thin Plate Splines and Principal Components Analysis the original data are summarised and the breast shape is described by a small set of numerical parameters.
Conference Paper
Virtual unrolling using X-ray computed tomography, Allegra D., Ciliberto E., Ciliberto P., Milotta F., Petrillo G., Stanco F., Trombato C., 2015 23rd European Signal Processing Conference, EUSIPCO 2015, 2015, pp. 2864-2868.
Cited by: 9
In recent years the virtual restoration of ancient papyri has become an important research challenge. This is because the papyrus degradation is often very serious, so physical analysis could damage the artifact. In this paper we address the problem of virtual unrolling to read papyrus scroll by avoiding a dangerous physical unrolling. To this aim we propose a virtual restoration method based on software manipulation of X-ray tomographic images. To test the proposed approach, a realistic papyrus model has been made using the ancient method and pigments compatible with the Egyptian use. The stack of 259 slices, obtained through X-Ray Tomography device, has been processed in order to obtain a digital unrolled papyrus that is quite similar to the hypothetical unrolled sheet.
Article
Automatic extraction of petrographic features from pottery of archaeological interest, Puglisi G., Stanco F., Barone G., Mazzoleni P., Journal on Computing and Cultural Heritage, 2015, vol. 8.
Cited by: 3
The microscopic description of ancient pottery is widely used for the fabric definition, classification and provenance assessment. In most cases, however, the description is qualitative. An improvement of the study of archaeological pottery needs a more objective approach with quantitative analysis. In classical scientific literature, the structural features and mineralogical composition of pottery are carried out on thin sections by means of transmitted polarized light microscope. The determination were obtained through observations with and without cross polarizator (nicols). The quantitative measurements are normally achieved with tedious and time consuming table with point counter. In this article the attention has been focused on the automatic identification of structural and textural components of the potteries through optical microscopy. Image analysis techniques have been then used to automatically classify the image components. Results confirm the effectiveness of the proposed approach: petrographic data collection becomes faster with respect to the traditional method providing also quantitative information useful for fabric recognition.
Conference Paper
A Semi-automatic Algorithm for Applying the Ken Burns Effect, Allegra D., Stanco F., Valenti G., Italian Chapter Conference 2015 - Smart Tools and Apps in Computer Graphics, STAG 2015, 2015, pp. 93-101.
Cited by: 0
In historical documentaries, video material often is not available. For this reason they are mainly made by using static material such as old photographs. To make this material more endearing and dynamic an effect known as “Ken Burns Effect” can be applied to the static images. It consists in a mix of panning and zooming effect applied to different objects which belong to an image. Hence, considerable user experience with photo and video editing software is required to successfully separate the objects from the background and to animate them to produce a high quality result. In this paper, we present an algorithm to apply Ken Burns effect with a minimal user interaction. The proposed solution exploits Statistical Region Merging segmentation algorithm to support the user in the process of separation of the objects from the background. Moreover, Inpainting algorithms are employed to fill the empty regions which becomes visible when an object is moved from its original position. Finally a random video can be produced from different “animated” images.
Book Chapter
A mobile application for Braille to black conversion, Farinella G., Leonardi P., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9386, pp. 741-751.
Cited by: 0
This work aims to the production of inclusive technologies to help people affected by diseases. In particular, we present a pipeline to convert Braille documents, acquired with a mobile device, into classic printed text. The mobile application has been thought as support for assistants (e.g., in the education domain) and parents of blind and partially sighted persons (e.g., children and elderly) for the reading of Braille written documents. The software has been developed and tested thanks to the collaboration with experts in the field [2]. Experimental results confirm the effectiveness of the proposed imaging pipeline in terms of conversion accuracy, punctuation, and final page layout.
Conference Paper
An electronic travel aid to assist blind and visually impaired people to avoid obstacles, Milotta F., Allegra D., Stanco F., Farinella G., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9257, pp. 604-615.
Cited by: 10
When devices and applications provide assistance to people they become part of assistive technology. If the assistance is given to impaired people, then it is possible to refer those technologies as adaptive technologies. The main aims of these systems are substitution of physical assistants and the improvement of typical tools already available for impaired people. In this paper some benefits and examples of adaptive technology applications will be discussed. Moreover we present an adaptive technology framework to avoid obstacles to be exploited by visually impaired and blind people. The proposed assistive technology has been designed to perform vision substitution; specifically it provides Electronic Travel Aid (ETA) capabilities through the processing of information acquired with a depth sensor such that the user can avoid obstacles during the environment exploration. In the proposed system we require to know just the height of the sensor with respect to the ground floor to calibrate the ETA system. Experiments are performed to asses the proposed system.
Conference Paper
On the exploitation of one class classification to distinguish food Vs non-food images, Farinella G.M., Allegra D., Stanco F., Battiato S., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9281, pp. 375-383.
Cited by: 17
In the last years automatic food image understanding has become an important research challenge for the society. This is because of the serious impact that food intake has in human life. Food recognition engines, can help the monitoring of the patient diet and his food intake habits. Nevertheless, distinguish among different classes of food is not the first question for assisted dietary monitoring systems. Prior to ask what class of food is depicted in an image, a computer vision system should be able to distinguish between food vs non-food images. In this work we consider one-class classification method to distinguish food vs non-food images. The UNICT-FD889 dataset is used for training purpose, whereas other two datasets of food and non-food images has been downloaded from Flickr to test the method. Taking into account previous works, we used Bag-of-Words representation considering different feature spaces to build the codebook. To give possibility to the community to work on the considered problem, the datasets used in our experiments are made publicly available.
Conference Paper
A benchmark dataset to study the representation of food images, Farinella G.M., Allegra D., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 8927, pp. 584-599.
Cited by: 60
It is well-known that people love food. However, an insane diet can cause problems in the general health of the people. Since health is strictly linked to the diet, advanced computer vision tools to recognize food images (e.g. acquired with mobile/wearable cameras), as well as their properties (e.g., calories), can help the diet monitoring by providing useful information to the experts (e.g., nutritionists) to assess the food intake of patients (e.g., to combat obesity). The food recognition is a challenging task since the food is intrinsically deformable and presents high variability in appearance. Image representation plays a fundamental role. To properly study the peculiarities of the image representation in the food application context, a benchmark dataset is needed. These facts motivate the work presented in this paper. In this work we introduce the UNICT-FD889 dataset. It is the first food image dataset composed by over 800 distinct plates of food which can be used as benchmark to design and compare representation models of food images. We exploit the UNICT-FD889 dataset for Near Duplicate Image Retrieval (NDIR) purposes by comparing three standard state-of-the-art image descriptors: Bag of Textons, PRICoLBP and SIFT. Results confirm that both textures and colors are fundamental properties in food representation. Moreover the experiments point out that the Bag of Textons representation obtained considering the color domain is more accurate than the other two approaches for NDIR.
Conference Paper
Multi-modal digitalization of Cultural Heritage Artifacts, Stanco F., Gallo G., Cannata G., Lombardo M., Italian Chapter Conference 2014 - Smart Tools and Apps in Computer Graphics, STAG 2014, 2014, pp. 45-48.
Cited by: 0
Objects made of different media, paintings, marbles, clay and wooden objects, textiles etc., form the historical collections of most of the middle to medium sized Museums in Italy. This variety poses difficult challenges to these institutions when they face the digitalization of part of their patrimony. This paper provides a report of an ongoing inter-disciplinary experimental program for a digitalization effort to be carried out by one of such institution. Through the discussion of the digitalization of different objects obtained with the use and integration of different techniques we illustrate some of the lessons learned in transferring to the final intended users the graphical tools and the know-how previously acquired in a research laboratory.
Conference Paper
Automatic braille to black conversion, Stanco F., Buffa M., Farinella G., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, vol. 8249 LNAI, pp. 517-526.
Cited by: 2
The aim of this work is related to the production of inclusive technologies to help people affected by diseases, like the blindness. We present a complete pipeline to convert scanned Braille documents into classic printed text. The tool has been thought as support for assistants (e.g., in the education domain) and parents of blind and partially sighted persons (e.g., children and elderly) for the reading of Braille written documents. The software has been built and tested thanks to the collaboration with experts in the field [1]. Experimental results confirm the effectiveness of the proposed imaging pipeline in terms of conversion accuracy, punctuation, and final page layout. © Springer International Publishing Switzerland 2013.
Conference Paper
Detection and correction of mistracking in digitalized analog video, Stanco F., Allegra D., Milotta F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, vol. 8158 LNCS, pp. 218-227.
Cited by: 3
Nowadays video technology is basically digital, but in the last half century the most diffused devices have been analog magnetic tapes. Since this is an old storing technique, it is necessary to convert these data in digital form. Moreover, analog videos may be affected by particular defects, called drops. Despite there are many hardware to perform the digitalization, few implement the correction of drops. In this paper, the drop also known as "Mistracking" is focused. A method to detect and correct this artifact is developed. © 2013 Springer-Verlag.
Article
Beyond virtual replicas: 3D modeling and maltese prehistoric architecture, Stanco F., Tanasi D., Journal of Electrical and Computer Engineering, 2013.
Cited by: 10
In the past decade, computer graphics have become strategic for the development of projects aimed at the interpretation of archaeological evidence and the dissemination of scientific results to the public. Among all the solutions available, the use of 3D models is particularly relevant for the reconstruction of poorly preserved sites and monuments destroyed by natural causes or human actions. These digital replicas are, at the same time, a virtual environment that can be used as a tool for the interpretative hypotheses of archaeologists and as an effective medium for a visual description of the cultural heritage. In this paper, the innovative methodology and aims and outcomes of a virtual reconstruction of the Borg in-Nadur megalithic temple, carried out by Archeomatica Project of the University of Catania, are offered as a case study for a virtual archaeology of prehistoric Malta. © 2013 Filippo Stanco and Davide Tanasi.
Conference Paper
Computer graphics solutions for pottery colors specification, Stanco F., Gueli A., Proceedings of SPIE - The International Society for Optical Engineering, 2013, vol. 8660.
Cited by: 8
The objective and repeatable measurement of the color of artifacts is a much needed practice in archeological research. Indeed, in many cases, color information are crucial for the interpretation of cultural products. To avoid the risks of a too subjective autoptic recognition, Munsell system is commonly adopted. This method requires that a human operator matches the perceived color to its standardized version in Munsell Charts. This approach has significant limitations that can mislead archaeologists in their daily work. The alternative would be the use of accurately calibrated sensors in a controlled illumination environment. These commodities are rarely available for most of the "on field" studies. In this paper a simple, economical, based on consumer level electronics and sensors, semi-automatic method of color detection on accurately and precisely selected regions of digital images of ancient pottery is presented. The proposed method indeed uses only the data from a common CCD sensor supported by a simple color measurement pipeline. Our tool is aimed to prevent subjective errors during color identification and to speed up the process of identification itself. The results obtained and percentages of successful matching with human Munsell color identification have statistically shown that our proposal is an interesting starting point to develop a full, cheap, easy to use system that could facilitate some aspects of the archaeologist's work. © 2013 SPIE-IS&T.
Conference Paper
Automatic petrographic feature extraction from pottery of archaeological interest, Puglisi G., Stanco F., Barone G., Mazzoleni P., International Symposium on Image and Signal Processing and Analysis, ISPA, 2013, pp. 548-551.
Cited by: 6
The concept of fabric, defined by the description and classification method introduced by Whitbread (1995), has been usually used to perform petrographic studies of thin sections of ancient ceramics. This work analyzes pottery of archaeological interest by making use of image processing algorithms. First a preliminary petrographic analysis has been quantitatively performed by point counter stage. Afterward our attention has been focused on the automatic identification of structural and textural components of the potteries through optical microscopy. Image analysis techniques have been then used to automatically classify the image component into three classes: inclusions, voids and groundmass. Preliminary results, confirm the effectiveness of the proposed approach: petrographic data collection becomes faster with respect to traditional method providing also quantitative information useful for fabric recognition. © 2013 University of Trieste and University of Zagreb.
Conference Paper
Computer graphics solutions for dealing with colors in archaeology, Stanco F., Tanasi D., Gueli A., Stella G., 6th European Conference on Colour in Graphics, Imaging, and Vision 2012, CGIV 2012, 2012, pp. 97-101.
Cited by: 8
A main issue in the archaeological research is to deal with colors of soils and artefacts, especially pottery. Since, in many cases, color information are crucial for the interpretation of cultural products, to avoid risks of a too subjective autoptic recognition Munsell system is commonly used in archaeology. This method widely used in other fields, like geology and anthropology, is based on the matching between the real color and its standardized version on Munsell Charts. But it has significant limitations, due to the influence of cultural background, color sensibility and education, that can mislead archaeologists in their daily work. In this paper a semi-automatic method of color detection on selected regions of digital images of ancient pottery is presented. This tool, whose encouraging experimental results are widely discussed in the contribute, is aimed to prevent eventual subjective errors during color identification and to speed up the process of identification itself. In order to emphasize the relativity of Munsell system, a statistical analysis was carried out on a group of potsherds selected for this research, pointing out the range of different colors identified on a single specimen by different observers. The starting point of the experiment was to take digital pictures of specimens together with the Gretag-Macbeth Color Checker Chart, whose chromatic values have been objectively established. The digital image is processed with color balancing techniques aimed to restore the original value of Macbeth patches, in order to eliminate distortions coming from acquisition process. After the color correction, several regions of interest are selected via 'point and click' for the identification of surface color, the algorithm converts RGB values in Munsell data. The reliability of our tool is also verified comparing this chromatic values with the color specification of pottery sherds performed with a spectrocolometer using the CIELAB space to evaluate the differences. The results obtained and percentages of successful matching with Munsell color identification coming from the statistical analysis, seem to open new perspectives for the development of a full automatic system with a GUI interface aimed to facilitate significantly some aspects of the archaeologist's work.
Article
Augmented perception of the past - The case of Hellenistic Syracuse, Stanco F., Tanasi D., Gallo G., Buffa M., Basile B., Journal of Multimedia, 2012, vol. 7, pp. 211-216.
Cited by: 31
The aim of this paper is to present a real-time interaction system for ancient artifacts digitally restored in a virtual environment. Using commercial hardware and open source software, Augmented Reality versions of archaeological artifacts are experienced on mobile devices both in a real outdoor site as well as an indoor museum. The case study for this project is represented by two artifacts of Syracuse, Italy, a statue and an altar, dated back to Hellenistic time. Virtual replicas of the two artifacts were produced applying different techniques. Later the two projects became part of the same research plan aimed to virtually rebuild the most significant artistic and architectural features of Hellenistic Syracuse. Besides the simple production of 3D models, via laserscanning and 3D modelling, a digital process of visual improvement of the statue was preliminary carried out based on photographic documentation of some archetypes. The commercial framework for mobile devices, ARToolworks, has been used for developing Augmented Reality applications. Using a pattern that is recognized by the device, the virtual model is shown as it is in the real world. The novelty of this work is that graduate students in virtual archaeology and non computer programmers such as museum staff, could benefit of this work and implement such a system. © 2012 ACADEMY PUBLISHER.
Conference Paper
Augmented perception of the past: The case of the Telamon from the Greek Theater of Syracuse, Stanco F., Tanasi D., Buffa M., Basile B., Communications in Computer and Information Science, 2012, vol. 247 CCIS, pp. 125-135.
Cited by: 9
The paper presents a system of real-time interaction with ancient artifacts digitally restored in a virtual environment in which the perception of reality is augmented, through the provision of the visual data missing in the current conditions of the artifacts themselves. The application of this system will be through common mobile devices, like the Apple Iphone. The case study for this project is a Late Classical Greek statue of a Telamon from the Theater of Syracuse. Since the statue is subject to constant degradation, a virtual replica was created through the application of laser scanning techniques. Once the 3D model of the Telamon was produced, a process of digital restoration based on archetypes and photographic documentation of the statue was carried out. Then, the commercial framework for mobile devices, ARToolworks, was used for developing Augmented Reality applications. Using a pattern that is recognized by the device, a three-dimensional model is associated to that pattern and the virtual model is shown as it is in the real world. © 2012 Springer-Verlag Berlin Heidelberg.
Conference Paper
Automatic color detection of archaeological pottery with Munsell system, Stanco F., Tanasi D., Bruna A., Maugeri V., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, vol. 6978 LNCS, pp. 337-346.
Cited by: 13
A main issue in the archaeological research is the identification of colored surfaces and soils through the application of Munsell system. This method widely used also in other fields, like geology and anthropology, is based on the subjective matching between the real color and its standardized version on Munsell chart. For preventing many possible errors caused by the subjectivity of the system itself, in this paper an automatic method of color detection on selected regions of digital images of archaeological pottery is presented. © 2011 Springer-Verlag.
Conference Paper
An improved image re-indexing technique by self organizing motor maps, Battiato S., Rundo F., Stanco F., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, vol. 5646 LNCS, pp. 62-70.
Cited by: 1
The paper presents a novel Motor Map neural network for re-indexing color mapped images. The overall learning process is able to smooth the local spatial redundancy of the indexes of the input image. Differently than before, the proposed optimization process is specifically devoted to re-organize the matrix of differences of the indexes computed according to some predefined patterns. Experimental results show that the proposed approach achieves good performances both in terms of compression ratio and zero order entropy of local differences. Also its computational complexity is competitive with previous works in the field. © 2009 Springer Berlin Heidelberg.
Conference Paper
The archeomatica project: Towards a new application of the computer graphics in archaeology, Sangregorio E., Stanco F., Tanasi D., 6th Eurographics Italian Chapter Conference 2008 - Proceedings, 2008, pp. 1-5.
Cited by: 5
In this paper the project Archeomatica of Catania University dedicated to Minoan civilization and Cretan culture is presented. The project carried out by experts of information technology and archaeological research provides the creation of realistic 3D models based on the data recorded during excavations that are digital upgradeable archives to add to the traditional graphic and photographic documentations. In particular two case-studies of 3D reconstructions of monuments of prehistoric and proto-historic archaeology, realized by a "philological approach", are presented. © The Eurographics Association 2008.
Article
Self organizing motor maps for color-mapped image re-indexing, Battiato S., Rundo F., Stanco F., IEEE Transactions on Image Processing, 2007, vol. 16, pp. 2905-2915.
Cited by: 26
Palette re-ordering is an effective approach for improving the compression of color-indexed images. If the spatial distribution of the indexes in the image is smooth, greater compression ratios may be obtained. As is already known, obtaining an optimal re-indexing scheme is not a trivial task. In this paper, we provide a novel algorithm for palette re-ordering problem making use of a motor map neural network. Experimental results show the real effectiveness of the proposed method both in terms of compression ratio and zero-order entropy of local differences. Also, its computational complexity is competitive with previous works in the field. © 2007 IEEE.
Conference Paper
ALZ: Adaptive learning for zooming digital images, Battiato S., Rundo F., Stanco F., Digest of Technical Papers - IEEE International Conference on Consumer Electronics, 2007.
Cited by: 22
In this paper a new method for zooming color images is proposed. It is based on a self organizing system that runs as "intelligent" assistant during the enlargment processing. The algorithm proposed uses local gradient estimation and gives results that have sharpness and computation time better than classical and recent techniques. © 2007 IEEE.
Article
Technique to correct yellowing and foxing in antique books, Stanco F., Tenze L., Ramponi G., IET Image Processing, 2007, vol. 1, pp. 123-133.
Cited by: 12
New algorithms for the automatic restoration of antique documents affected by foxing and by yellowing deterioration processes are proposed in the paper. The physical restoration of such objects is both expensive and hard to carry out by nonspecialised library personnel. The proposed algorithms ensure fast and less expensive results, and can be used also by nonqualified operators. Moreover, these techniques improve the performance of optical character recognition operators. © The Institution of Engineering and Technology 2007.
Conference Paper
A new descreening technique in the frequency domain, Battiato S., Stanco F., 4th Eurographics Italian Chapter Conference 2006 - Proceedings, 2006, pp. 137-142.
Cited by: 1
In this paper a new algorithm to obtain a continuous tone image starting from a halftoned one is proposed. This de-screening technique is based on Butterworth filtering in the frequency domain. It removes the pattern of the original screen leaving unchanged the colors in the image. The proposed algorithm ensures fast and effective results, and can be used also by non-qualified operators. © 2006 The Eurographics Association.
Conference Paper
Color palette images re-indexing by self organizing Motor Maps, Battiato S., Rundo F., Stanco F., 4th Eurographics Italian Chapter Conference 2006 - Proceedings, 2006, pp. 241-246.
Cited by: 2
Palette re-ordering is a well known and very effective approach for improving the compression of color-indexed images. If the spatial distribution of the indexes in the image is smooth, greater compression ratios may be obtained. As known, obtaining an optimal re-indexing scheme is not a simple problem. In this paper we provide a novel algorithm for palette re-ordering problem showing the advantages of using a neural network instead of classical heuristic methods. We propose to apply the Motor Map neural network which is considered an extension of the well-known SOM Kohonen neural network. Experiments confirm the effectiveness of the proposed technique. © 2006 The Eurographics Association.
Editorial
Preface, Battiato S., Gallo G., Stanco F., 4th Eurographics Italian Chapter Conference 2006 - Proceedings, 2006, pp. 5.
Cited by: 0
Conference Paper
Visibility based detection and removal of semi-transparent blotches on archived documents, Bruni V., Crawford A., Vitulano D., Stanco F., VISAPP 2006 - Proceedings of the 1st International Conference on Computer Vision Theory and Applications, 2006, vol. 1, pp. 64-71.
Cited by: 14
This paper focuses on a novel model for digital suppression of semi-transparent blotches, caused by the contact between water and paper of antique documents. The proposed model is based on laws regulating the human visual system and provides a fast and automatic algorithm both in detection and restoration. Experimental results show the great potentialities of the proposed model in solving also critical situations.
Conference Paper
A novel image re-indexing by self organizing Motor Maps, Battiato S., Rundo F., Stanco F., Proceedings - International Conference on Image Processing, ICIP, 2006, vol. 6.
Cited by: 1
Palette re-ordering is a well known and very effective approach for improving the compression of color indexed images. If the spatial distribution of the indexes in the image is smooth, greater compression ratios may be obtained. As known, obtaining an optimal re-indexing scheme is not a trivial task. In this paper we provide a novel algorithm for palette re-ordering problem making use of a Motor Map neural network. Experimental results show the real effectiveness of the proposed method both in terms of compression ratio and zeroorder entropy of local differences. Also its computational complexity is competitive with previous works in the field. © 2007 IEEE.
Article
Virtual restoration of vintage photographic prints affected by foxing and water blotches, Stanco F., Tenze L., Ramponi G., Journal of Electronic Imaging, 2005, vol. 14.
Cited by: 32
We propose a new algorithm to digitally restore vintage photographic prints affected by foxing and water blotches. It semi-automatically recovers the defects utilizing the features of the stains. The restoration process enhances the residual image information still present in the area. It is composed of three different steps: inpainting, additive-multiplicative (A-M) modeling, and interpolation. © 2005 SPIE and IS&T.
Conference Paper
An improved method for water blotches detection and restoration, Stanco F., Tenze L., De Rosa A., Proceedings of the Fourth IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2004, 2004, pp. 457-460.
Cited by: 4
In this paper an algorithm to digitally restore vintage photographic prints affected by water blotches is proposed. The algorithm uses a new simple and effective semiautomatic detection, and a smart restoration method based on an additive/multiplicative model. The obtained results show that these defects are completely removed without producing significant artifacts. ©2004 IEEE.
Conference Paper
Virtual restoration of fragmented glass plate photographs, Stanco F., Tenze L., Ramponi G., De Polo A., Proceedings of the Mediterranean Electrotechnical Conference - MELECON, 2004, vol. 1, pp. 243-246.
Cited by: 13
In this paper we address the problem of restoration of fragmented glass plate photographs. We propose an algorithm based on the roto-translation of the fragments. A preprocessing adjustment in the contour combined with final interpolation are necessary to avoid artifacts.
Article
An efficient re-indexing algorithm for color-mapped images, Battiato S., Gallo G., Impoco G., Stanco F., IEEE Transactions on Image Processing, 2004, vol. 13, pp. 1419-1423.
Cited by: 36
The efficiency of lossless compression algorithms for fixed-palette images (indexed images) may change if a different indexing scheme is adopted. Many lossless compression algorithms adopt a differential-predictive approach. Hence, if the spatial distribution of the indexes over the image is smooth, greater compression ratios may be obtained. Because of this, finding an indexing scheme that realizes such a smooth distribution is a relevant issue. Obtaining an optimal re-indexing scheme is suspected to be a hard problem and only approximate solutions have been provided in literature. In this paper, we restate the re-indexing problem as a graph optimization problem: an optimal re-indexing corresponds to the heaviest Hamiltonian path in a weighted graph. It follows that any algorithm which finds a good approximate solution to this graph-theoretical problem also provides a good re-indexing. We propose a simple and easy-to-implement approximation algorithm to find such a path. The proposed technique compares favorably with most of the algorithms proposed in literature, both in terms of computational complexity and of compression ratio. © 2004 IEEE.
Conference Paper
'Foxing' in vintage photographs: Detection and removal, Stanco F., Tenze L., Ramponi G., European Signal Processing Conference, 2004, vol. 06-10-September-2004, pp. 493-496.
Cited by: 3
In this paper a new algorithm to digitally restore vintage photographic prints affected by the 'foxing' defect is proposed. The algorithm is composed of several automatic and consecutive steps where detection of damaged areas is coupled with removal methods. The restoration algorithms are based on an inpainting technique and on an additive/multiplicative model. The first one replaces the lost data; the second one fixes the defective area searching for optimal parameters around the damaged area. The obtained results show that the foxing spots are completely removed without producing significant artifacts.
Conference Paper
Smart interpolation by anisotropic diffusion, Battiato S., Gallo G., Stanco F., Proceedings - 12th International Conference on Image Analysis and Processing, ICIAP 2003, 2003, pp. 572-577.
Cited by: 46
To enlarge a digital image from a single frame preserving the perceptive cues is a relevant research issue. The best known algorithms take into account the presence of edges in the luminance channel, to interpolate correctly the samples/pixels of the original image. This approach allows the production of pictures where the interpolated artifacts (aliasing blurring effect,.) are limited but where high frequencies are not properly preserved. The zooming algorithm proposed in this paper on the other hand reduces the noise and enhances the contrast to the borders/edges of the enlarged picture using classical anisotropic diffusion improved by a smart heuristic strategy. The method requires limited computational resources and it works on gray-level images, RGB color pictures and Bayer data. Our experiments show that this algorithm outperforms in quality and efficiency the classical interpolation methods (replication, bilinear, bicubic). © 2003 IEEE.
Conference Paper
Automatic discrimination of text images, Alessi N.G., Battiato S., Gallo G., Mancuso M., Stanco F., Proceedings of SPIE - The International Society for Optical Engineering, 2003, vol. 5017, pp. 351-359.
Cited by: 9
This paper introduces a method for the automatic discrimination of digital images based on their semantic content. The proposed system allows to detect if a digital image contains or not a text. This is realized by a multi-steps procedure based on low-level features set properly derived. Our experiments show that the proposed algorithm is competitive in efficiency with classical techniques, and it has a lower complexity.
Conference Paper
Towards the automated restoration of old photographic prints: A survey, Stanco F., Ramponi G., De Polo A., IEEE Region 8 EUROCON 2003: Computer as a Tool - Proceedings, 2003, vol. B, pp. 370-374.
Cited by: 33
The ubiquitous fruition of cultural and artistic heritage in the field of photography requires as a first step the conversion of a huge amount of old printed material into digital form, for successive manipulation and data management This process is particularly delicate for photographic prints, which often show the effects of aging. This paper reports a list of the principal defects that can be detected in an old photography; the different origins of them, and their different features, suggest different restoration approaches.
Conference Paper
Analysis and characterization of super-resolution reconstruction methods, Battiato S., Gallo G., Mancuso M., Messina G., Stanco F., Proceedings of SPIE - The International Society for Optical Engineering, 2003, vol. 5017, pp. 323-331.
Cited by: 7
Reconstruction techniques exploit a first building process using Low-resolution (LR) images to obtain a "draft" High Resolution (HR) image and then update the estimated HR by back-projection error reduction. This paper presents different HR draft image construction techniques and shows methods providing the best solution in terms of final perceived/measured quality. The following algorithms have been analysed: a proprietary Resolution Enhancement method (RE-ST); a Locally Adaptive Zooming Algorithm (LAZA); a Smart Interpolation by Anisotropie Diffusion (SIAD); a Directional Adaptive Edge-Interpolation (DAEI); a classical Bicubic interpolation and a Nearest Neighbour algorithm. The resulting HR images are obtained by merging the zoomed LR-pictures using two different strategies: average or median. To improve the corresponding HR images two adaptive error reduction techniques are applied in the last step: auto-iterative and uncertainty-reduction.
Article
A locally adaptive zooming algorithm for digital images, Battiato S., Gallo G., Stanco F., Image and Vision Computing, 2002, vol. 20, pp. 805-812.
Cited by: 172
In this paper we address the problem of producing an enlarged picture from a given digital image (zooming). We propose a method that tries to take into account information about discontinuities or sharp luminance variations while doubling the input picture. This is realized by a nonlinear iterative procedure of the zoomed image and could hence be implemented with limited computational resources. The algorithm works on monochromatic images, RGB color pictures and Bayer data images acquired by CCD/CMOS camera sensor. Our experiments show that the proposed method beats in quality classical simple zooming techniques (e.g. pixel replication, simple interpolation). Moreover our algorithm is competitive both for quality and efficiency with bicubic interpolation. © 2002 Published by Elsevier Science B.V.
Conference Paper
A colour reindexing algorithm for lossless compression of digital images, Battiato S., Gallo G., Impoco G., Stanco F., Proceedings - Spring Conference on Computer Graphics, SCCG 2001, 2001, pp. 104-108.
Cited by: 9
The efficiency of lossless compression algorithms for fixed palette images (also called indexed images) changes if a different indexing scheme is adopted. Indeed, these algorithms adopt a differential-predictive approach of some sort: if the spatial distribution of the indexes over the image is smooth, greater compression ratios may be obtained. It hence becomes relevant to find an indexing scheme that realizes such a smooth distribution. This seems to be a hard problem, and only approximate answers can be provided if a realistic run-time has to be achieved. In this paper, we propose a new indexing scheme, based on an approximate algorithm that maximizes the cost of a Hamiltonian path in a weighted graph. The proposed technique compares favourably with the algorithm proposed by W. Zeng et al. (2000). The computational complexity of the two algorithms is compared and experimental tests that show that relative compression rates are reported.

Progetti


Archeomatica

Nel 2007 l'Image Processing Lab dell'Università degli Studi di Catania ha avviato un programma di ricerca di archeologia digitale denominato progetto Archeomatica, finalizzato a produrre modelli 3D di siti archeologici preistorici con un alto livello di accuratezza, grazie ai dati acquisiti durante gli scavi. Da quel momento il progetto è cresciuto molto. Al giorno d'oggi, all'interno del progetto vengono trattati diversi argomenti, come restauro digitale, scansione 3D, realtà aumentata, specifica del colore, riconoscimento delle forme, tour virtuali, digitalizzazione di archivi testuali e sezioni sottili.
Il progetto Archeomatica è pronto a rispondere alla necessità di digitalizzazione nel campo dei Beni Culturali ed alla realizzazione di nuovi servizi interattivi per visitatori e studiosi.


Arrowhead FPVN

Coordinatore dell’Unità dell’Università di Catania del progetto europeo AFPVN-Arrowhead FPVN, Key Digital Technologies Joint Undertaking - 2022 next Generation EU HORIZON-KDT-JU-2022-1-IA - Capofila: Leonardo S.p.A., Partecipanti: Eurotech S.p.A, Fondazione Bruno Kessler, Politecnico di Torino, Università di Catania, Università di Genova.


PNRR - SAMOTHRACE

Task leader per il Task 3 – “Fruition and Spaces” nell’ambito del progetto SAMOTHRACE “SiciliAn MicronanOTecH Research And Innovation CEnter” – Ecosistema dell’innovazione (PNRR, Mission 4, Component 2 Investment 1.5, Avviso n. 3277 del 30-12-2021), nell’ambito delle attività dello Spoke 1 – Università di Catania del Work Package 6 Cultural Heritage, con un impegno orario pari a 3 mesi uomo/ anno per un totale di 9 mesi. Periodo e luogo di svolgimento: 01 ottobre 2022 – 30 settembre 2025 –DMI.


PNRR - CHANGES

Partecipante al progetto PE5 dal titolo “CHANGES – Cultural Heritage Active Innovation for Sustainable Society” finanziato nell’ambito del PNNR, Missione 4 “Istruzione e ricerca” – Componente 2 “Dalla ricerca all’impresa” – Investimento 1.3, finanziato dall’Unione europea – Next GenerationEU (Avviso n. 341 del 15.03.2022), nell’ambito dello SPOKE 6 “History, Conservation and Restoration of Cultural Cultural Heritage”, WP1 – Anamnesis / WP2 Knowlegde / WP3 Restoration / WP4 Monitoring / WP5 Sharing, guidato dall’Università di Catania, per la realizzazione dell’attività di ricerca “Sviluppo di metodologia e tecniche applicate alla anamnesi di contesti archeologici pluristratificati come strumento di conoscenza per le successive fasi di restauro, monitoraggio e condivisione dei dati alla comunità scientifica e alla società” da effettuare presso il Dipartimento di Scienze Umanistiche - DISUM nel periodo 1 dicembre 2022 – 30 novembre 2025.


DREAMIN

Il progetto DREAMIN - Digital REmote Access to Museums and research INfrastructures - ha come obiettivo quello di fornire un accesso digitale da remoto a musei e centri di ricerca universitari.
Uno degli output del progetto è il Digital HUB, una piattaforma multimediale grazie alla quale è possibile consultare tutti i risultati del progetto.


PNRR - OUI

Partecipante al progetto Orientamento “OUI, ovunque da qui”, PNRR, MISSIONE 4 “Istruzione e ricerca”, COMPONENTE 1 “Potenziamento dell’offerta dei servizi all’istruzione: dagli asili nido all’Università”, INVESTIMENTO 1.6 “Orientamento attivo nella transizione scuola-università”.


DELIAS

P.O.N. Sviluppo e Applicazioni di Materiali e Processi Innovativi per la Diagnostica e il Restauro di Beni Culturali (DELIAS), codice progetto PON03PE_00214_2


“DL4Health”

PO FESR 2014/2020 - Azione 1.1.5. del POR FESR Sicilia 2014/2020


V.E.D.I.

Vision Exploitation for Data Interpretation (PON MISE Horizon 2020)


EUNICE

(European University For Customised Education), Unità di Catania, Granted by: Erasmus+ Programme of the European Union


SATURN

SMART MANUFACTURING (SATURN) - SATURN – Smart mAnufacTURiNg – Progetto MISE PON Fabbrica Intelligente.


FARM.PRO

(PO/FESR Misura 4.1.1.1)


IT@CHA

The partners involved in this project are: DMI, University of Catania and TECHLABWorks


EMOCUBE

(PO/FESR Misura 4.1.1.2 – Regione Sicilia)


DIGINTEGRA

(PO/FESR Misura 4.1.1.1 – Regione Sicilia)


PANORAMA

Ultrawide Context Aware Imaging (ENIAC Programme).


COST Action 276

“Information and Knowledge Management for Integrated Media Communication”


PIACERI

Piano della Ricerca 2016-2018 – linea di intervento 2 “Tecniche Digitali Di Trattamento Del Colore In Ambito Archeologico”


PO FESR 2014- 2020: 671 672

"Fruizione digitale del Monastero dei Benedettini e del Museo della Fabbrica".


PIACERI 2

Piano di incentivi per la ricerca di Ateneo 2020/2022 (Pia.ce.ri.) codice 53722122152 – linea 2 “CLEAR CoLor rEndering Accuracy in cultuRal heritage”


PO FESR - SALIRE

Partecipante al progetto SALIRE – Sound Algorithms for Low-latency Intelligent Recognition of Event – PO FESR SICILIA 2014-2020 – Azione 1.1.5. Partner: Trilogic srl (leading), Noviacom soc.coop., Medilink srl, UNICT


CHANCE

Piano Per La Ricerca 2016-2018 - Linea di Intervento 1 "Chance" II Edizione - Prof. F. Stanco, codice progetto 53725122122


Fulbright

Responsabile Scientifico per il progetto Fulbright “Community GIS and Heritage Preservation: Social and Economic Change in Sicily after Rome”, Partner Fondazione con il Sud, University of South Forida, A.A. 2022-23


MISS 2018

The focus of this Medical Imaging Summer School (MISS) is to train a new generation of young scientists to bridge this gap, by providing insights into the various interfaces between medical imaging and deep learning, based on the shared broad categories of medical image computing, computer-aided image interpretation and disease classification.


Libri


cover

Digital Imaging for Cultural Heritage Preservation

Analysis, Restoration, and Reconstruction of Ancient Artworks

Filippo Stanco, Sebastiano Battiato, Giovanni Gallo

ISBN: 978-1-4398217-3-2
Published July 28th 2011 by CRC Press – 523 pages
Series: Digital Imaging and Computer Vision

cover

Elaborazione delle Immagini Digitali

R. Gonzalez e R. Woods, traduzione a cura di S. Battiato e F. Stanco

ISBN: 978-88-7192-506-6
Pearson 2008
Costo euro 53,00

Disponibile presso tutte le librerie

cover

Radamante al computer. Archeologia e informatica nel mondo minoioco: l'esperienza catanese

G. Gallo, V. La Rosa, F. Stanco, D. Tanasi

ISBN: 978-88-905786-0-1

cover

Fondamenti di Image Processing, Guida teorico/pratica per l'elaborazione e la codifica di immagini digitali

S. Battiato, F. Stanco

ISBN: 88-88659-49-8
EdiArgo 2006

Disponibile presso laboratorio IPLab