Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29293
Title: Designing and evaluating an expert system for restoring damaged byzantine icons
Authors: Maronidis, Anastasios 
Voutounos, Chrysanthos 
Lanitis, Andreas 
Major Field of Science: Engineering and Technology;Social Sciences
Field Category: Computer and Information Sciences;Arts;Design
Keywords: Damage detection;Shape restoration;Texture restoration;Expert system;Icon restoration;Statistical appearance models
Issue Date: Nov-2015
Source: 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
Journal: Multimedia Tools and Applications 
Abstract: 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
Appears in Collections:Άρθρα/Articles

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