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https://hdl.handle.net/20.500.14279/29293
Τίτλος: | Designing and evaluating an expert system for restoring damaged byzantine icons | Συγγραφείς: | Maronidis, Anastasios Voutounos, Chrysanthos Lanitis, Andreas |
Major Field of Science: | Engineering and Technology;Social Sciences | Field Category: | Computer and Information Sciences;Arts;Design | Λέξεις-κλειδιά: | Damage detection;Shape restoration;Texture restoration;Expert system;Icon restoration;Statistical appearance models | Ημερομηνία Έκδοσης: | Νοε-2015 | Πηγή: | Multimedia Tools and Applications: An International Journal, 2015, v.74, no.21, p.p. 9747-9770 | Volume: | 74 | Issue: | 21 | Start page: | 9747 | End page: | 9770 | Περιοδικό: | Multimedia Tools and Applications | Περίληψη: | The use of image processing techniques in cultural heritage applications has been gaining increasing interest in the research community. In this paper, an integrated framework that can be used for virtual restoration of the facial region of damaged Byzantine icons is presented. A key aspect of the proposed methodology is the integration of practices adopted by expert icon restorers into a machine-based expert system that incorporates the modules of damage detection, shape and texture restoration. Damage detection is performed based on a residual-based approach, while the shape restoration method utilizes a 3D shape model generated by incorporating a set of geometrical rules defined by expert Byzantine style iconographers. Texture restoration is based on the recursive Principal Component Analysis (PCA) technique so that combinations of colors learned from a training set are applied to the damaged icon regions. All modules, developed as part of this framework, are incorporated into a user-friendly application that can be used by amateurs or professional Byzantine icon restorers and conservators. The potential of the developed tool has been validated through a quantitative experimental process and a user-based evaluation. | URI: | https://hdl.handle.net/20.500.14279/29293 | ISSN: | 13807501 15737721 |
DOI: | 10.1007/s11042-014-2149-1 | Rights: | © 2023 Springer Nature | Type: | Article | Affiliation: | Cyprus University of Technology | Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | Άρθρα/Articles |
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