Title: Intelligent system for cultural objects identification, damage assessment and restoration

Authors: Evangelos Sakkopoulos; Erion-Vasilis Pikoulis; Emmanouil Viennas; Nikolaos Nodarakis; Eleni Cheilakou; Amani-Christiana Saint; Maria Koui; Athanasios Tsakalidis

Addresses: Graphics, Multimedia and GIS System Lab, Computer Engineering and Informatics Department, University of Patras, GR-26504 Rio Patras, Greece ' Graphics, Multimedia and GIS System Lab, Computer Engineering and Informatics Department, University of Patras, GR-26504 Rio Patras, Greece ' Graphics, Multimedia and GIS System Lab, Computer Engineering and Informatics Department, University of Patras, GR-26504 Rio Patras, Greece ' Graphics, Multimedia and GIS System Lab, Computer Engineering and Informatics Department, University of Patras, GR-26504 Rio Patras, Greece ' Department of Materials Science and Engineering, NDT Lab, School of Chemical Engineering, National Technical University of Athens, Greece ' Department of Materials Science and Engineering, NDT Lab, School of Chemical Engineering, National Technical University of Athens, Greece ' Department of Materials Science and Engineering, NDT Lab, School of Chemical Engineering, National Technical University of Athens, Greece ' Graphics, Multimedia and GIS System Lab, Computer Engineering and Informatics Department, University of Patras, GR-26504 Rio Patras, Greece

Abstract: Cultural objects and art works need ongoing conservation interventions in order to be available for the next generations. The most object-friendly analysis approaches are based on non-destructive techniques (NDTs) that allow both the materials characterisation as well as the decay detection of cultural artefacts. Non-destructive testing and evaluation includes the employment of several methods such as the well-established technique of diffuse reflectance spectroscopy with fibre optics (FORS). Such techniques produce output with multiple series of data for multiple different pigment used in objects. In this work, we present a data management solution that contributes with: 1) a library of known reference pigments/colours; 2) a proposed pattern matching technique that allows the automatic classification of any new pigment. The experimental evaluation results show that the data processing proposed is effective. Feedback is particularly encouraging as it allows automation and therefore radically decreased time for pigment/colour matching and identification.

Keywords: fibre optics diffuse reflectance spectroscopy; FORS; intelligent management systems; non-destructive techniques; NDT; NDT image analysis.

DOI: 10.1504/IJIIDS.2017.087246

International Journal of Intelligent Information and Database Systems, 2017 Vol.10 No.3/4, pp.224 - 245

Available online: 14 Sep 2017 *

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