Multi-Temporal Image Analysis for Preventive Conservation of Historical Musical Instruments

Artworks need to be constantly monitored to check their state of conservation and to quickly spot the eventual presence of alterations or damages. Preventive conservation is the set of practices employed to reach this goal. Unfortunately, this results generally in a cumbersome process involving multiple analytical techniques. Consequently, methods able to provide a quick preliminary examination of the artworks (e.g., optical monitoring) seem very promising to streamline preventive conservation procedures. We are especially interested in the study of historical wood musical instruments, a kind of artwork particularly subject to mechanical wear since they are both held in museums and also occasionally played in concerts. Our primary goal is to detect possible altered regions on the surface of the instruments early and thus provide the experts some precise indications on where to apply more in-depth examinations to check for potential damages. In this work, we propose an optical monitoring method based on the a-contrario probabilistic framework. Tests were conducted on the “Violins UVIFL imagery” dataset, a collection of UV-induced fluorescence image sequences of artificially altered wood samples and violins. Obtained results showed the robustness of the proposed method and its capability to properly detect altered regions while rejecting noise.