Intelligent system for cultural objects identification, damage assessment and restoration. (2017) - Sakkopoulos, Evangelos; Pikoulis, Erion-Vasilis; Viennas, Emmanouil; Nodarakis, Nikolaos; Cheilakou, Eleni; Saint, Amani-Christiana; Koui, Maria; Tsakalidis, Athanasios
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.