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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bradley, S.: Preventive conservation research and practice at the British museum. J. Am. Inst. Conserv. 44(3), 159–173 (2005). https://doi.org/10.1179/019713605806082248
Brandmair, B., Greiner, P.S.: Stradivari varnish: scientific analysis of his finishing technique on selected instruments. Serving Audio (2010)
Bruni, S., Guglielmi, V.: Identification of archaeological triterpenic resins by the non-separative techniques FTIR and 13C NMR: the case of Pistacia resin (mastic) in comparison with frankincense. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 121, 613–622 (2014). https://doi.org/10.1016/j.saa.2013.10.098
Cerra, D., Plank, S., Lysandrou, V., Tian, J.: Cultural heritage sites in danger–towards automatic damage detection from space. Remote Sens. 8(9), 781 (2016). https://doi.org/10.3390/rs8090781
Chouhan, S.S., Kaul, A., Singh, U.P.: Soft computing approaches for image segmentation: a survey. Multimedia Tools Appl. 77(21), 28483–28537 (2018). https://doi.org/10.1007/s11042-018-6005-6
Deborah, H., Richard, N., Hardeberg, J.Y.: Hyperspectral crack detection in paintings. In: 2015 Colour and Visual Computing Symposium (CVCS), pp. 1–6, August 2015. https://doi.org/10.1109/CVCS.2015.7274902
Dondi, P., Lombardi, L., Invernizzi, C., Rovetta, T., Malagodi, M., Licchelli, M.: Automatic analysis of UV-induced fluorescence imagery of historical violins. J. Comput. Cult. Herit. 10(2), 12:1–12:13 (2017). https://doi.org/10.1145/3051472
Dondi, P., Lombardi, L., Malagodi, M., Licchelli, M.: Automatic identification of varnish wear on historical instruments: the case of Antonio Stradivari violins. J. Cult. Herit. 22, 968–973 (2016). https://doi.org/10.1016/j.culher.2016.05.010
Dondi, P., Lombardi, L., Malagodi, M., Licchelli, M., Rovetta, T., Invernizzi, C.: An interactive tool for speed up the analysis of UV images of Stradivari violins. In: Murino, V., Puppo, E., Sona, D., Cristani, M., Sansone, C. (eds.) ICIAP 2015. LNCS, vol. 9281, pp. 103–110. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23222-5_13
Fichera, G.V., et al.: Innovative monitoring plan for the preventive conservation of historical musical instruments. Stud. Conserv. 63(Suppl. 1), 351–354 (2018). https://doi.org/10.1080/00393630.2018.1499853
Fiocco, G., et al.: Approaches for detecting madder lake in multi-layered coating systems of historical bowed string instruments. Coatings 8(5) (2018). https://doi.org/10.3390/coatings8050171
Janssens, K., Van Grieken, R.: Non-Destructive Micro Analysis of Cultural Heritage Materials, vol. 42. Elsevier, Amsterdam (2004)
Jmal, M., Souidene, W., Attia, R.: Efficient cultural heritage image restoration with nonuniform illumination enhancement. J. Electron. Imaging 26(1), 1–15 (2017). https://doi.org/10.1117/1.JEI.26.1.011020
Paulinas, M., Ušinskas, A.: A survey of genetic algorithms applications for image enhancement and segmentation. Inf. Technol. Control 36(3), 278–284 (2007)
Pizurica, A., et al.: Digital image processing of the Ghent Altarpiece: supporting the painting’s study and conservation treatment. IEEE Signal Process. Mag. 32(4), 112–122 (2015). https://doi.org/10.1109/MSP.2015.2411753
Polak, A., et al.: Hyperspectral imaging combined with data classification techniques as an aid for artwork authentication. J. Cultural Herit. 26, 1–11 (2017). https://doi.org/10.1016/j.culher.2017.01.013
Puzicha, J., Hofmann, T., Buhmann, J.M.: Non-parametric similarity measures for unsupervised texture segmentation and image retrieval. In: Proceedings of 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 267–272, June 1997. https://doi.org/10.1109/CVPR.1997.609331
Rovetta, T., et al.: The case of Antonio Stradivari 1718 ex-San Lorenzo violin: history, restorations and conservation perspectives. J. Archaeol. Sci. Rep. 23, 443–450 (2019). https://doi.org/10.1016/j.jasrep.2018.11.010
Rovetta, T., Invernizzi, C., Licchelli, M., Cacciatori, F., Malagodi, M.: The elemental composition of Stradivari’s musical instruments: new results through non-invasive EDXRF analysis. X-Ray Spectrom. 47(2), 159–170 (2018). https://doi.org/10.1002/xrs.2825
Stanco, F., Battiato, S., Gallo, G.: Digital Imaging for Cultural Heritage Preservation: Analysis, Restoration, and Reconstruction of Ancient Artworks. CRC Press, Boca Raton (2011)
Stuart, B.H.: Analytical Techniques in Materials Conservation. Wiley, Hoboken (2007)
Tan, W.R., Chan, C.S., Aguirre, H.E., Tanaka, K.: ArtGAN: artwork synthesis with conditional categorical GANs. In: 2017 IEEE International Conference on Image Processing (ICIP), pp. 3760–3764, September 2017. https://doi.org/10.1109/ICIP.2017.8296985
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-30754-7_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30753-0
Online ISBN: 978-3-030-30754-7
eBook Packages: Computer ScienceComputer Science (R0)
