Using Signal Processing and Semantic Web Technologies to Analyze Byzantine Iconography

A bottom-up approach for documenting art objects processes data from innovative nondestructive analysis with signal processing and neural network techniques to provide a good estimation of the paint layer profile and pigments of artwork. The approach also uses semantic Web technologies and maps concepts relevant to the analysis of paintings and Byzantine iconography to the Conceptual Reference Model of the International Committee for Documentation (CIDOC-CRM). This approach has introduced three main contributions: the development of an integrated nondestructive technique system combining spectroscopy and acoustic microscopy, supported by intelligent algorithms, for estimating the artworks' paint layers profile; mapping of analytical data pertinent to the diagnosis of art paintings to CIDOC-CRM to demonstrate how semantic Web technologies can benefit cultural heritage; and the introduction of a practical setting that combines different AI fields.