Abstract
Monitoring the state of conservation of a historical violin is a difficult task. Multiple restorations during centuries have created a very complex and stratified surface, hard to correctly interpret. Moreover, the reflectance of the varnishes and the rounded morphology of the violins can easily produce noise, that can be confused for a real alteration. To properly compare multi-temporal images of the same instrument a robust segmentation is needed. To reach this goal we adopted a genetic algorithm to evolve in this direction our previous segmentation method based on HSV histogram quantization. As test set we used images of two important violins held in “Museo del Violino” in Cremona (Italy), periodically acquired during a six-month period, and images of a sample violin altered in laboratory to reproduce a long-term evolution.
This work was partially granted by “Fondazione Arvedi-Buschini” of Cremona, Italy.
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Acknowledgements
We would like to thank “Fondazione Museo del Violino Antonio Stradivari”, “Friends of Stradivari” and “Cultural District of Violin Making of Cremona” for their collaboration.
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Dondi, P., Lombardi, L., Malagodi, M., Licchelli, M. (2019). Segmentation of Multi-temporal UV-Induced Fluorescence Images of Historical Violins. In: Cristani, M., Prati, A., Lanz, O., Messelodi, S., Sebe, N. (eds) New Trends in Image Analysis and Processing – ICIAP 2019. ICIAP 2019. Lecture Notes in Computer Science(), vol 11808. Springer, Cham. https://doi.org/10.1007/978-3-030-30754-7_9
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