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Open AccessArticle

Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography

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Department of Informatics, Modeling, Electronics and Systems Engineering, University of Calabria, Via P.Bucci, Arcavacata, 87036 Rende (CS), Italy
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Department of Engineering, Polo Scientifico Didattico di Terni, University of Perugia, 05100 Terni (TR), Italy
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Department of Industrial and Information Engineering and Economics, University of L’Aquila, 67100 L’Aquila (AQ), Italy
4
Restorer, Via Muranuove 64, 67043 Celano (AQ), Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(19), 4335; https://doi.org/10.3390/s19194335
Received: 4 September 2019 / Revised: 2 October 2019 / Accepted: 6 October 2019 / Published: 8 October 2019
The use of different spectral bands in the inspection of artworks is highly recommended to identify the maximum number of defects/anomalies (i.e., the targets), whose presence ought to be known before any possible restoration action. Although an artwork cannot be considered as a composite material in which the zero-defect theory is usually followed by scientists, it is possible to state that the preservation of a multi-layered structure fabricated by the artist’s hands is based on a methodological analysis, where the use of non-destructive testing methods is highly desirable. In this paper, the infrared thermography and hyperspectral imaging methods were applied to identify both fabricated and non-fabricated targets in a canvas painting mocking up the famous character “Venus” by Botticelli. The pulse-compression thermography technique was used to retrieve info about the inner structure of the sample and low power light-emitting diode (LED) chips, whose emission was modulated via a pseudo-noise sequence, were exploited as the heat source for minimizing the heat radiated on the sample surface. Hyper-spectral imaging was employed to detect surface and subsurface features such as pentimenti and facial contours. The results demonstrate how the application of statistical algorithms (i.e., principal component and independent component analyses) maximized the number of targets retrieved during the post-acquisition steps for both the employed techniques. Finally, the best results obtained by both techniques and post-processing methods were fused together, resulting in a clear targets map, in which both the surface, subsurface and deeper information are all shown at a glance. View Full-Text
Keywords: pulse-compression thermography; hyperspectral imaging; defects; cultural heritage; image processing; information fusion; painting on canvas; NDT; principal component analysis; independent component analysis pulse-compression thermography; hyperspectral imaging; defects; cultural heritage; image processing; information fusion; painting on canvas; NDT; principal component analysis; independent component analysis
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Laureti, S.; Malekmohammadi, H.; Rizwan, M.K.; Burrascano, P.; Sfarra, S.; Mostacci, M.; Ricci, M. Looking Through Paintings by Combining Hyper-Spectral Imaging and Pulse-Compression Thermography. Sensors 2019, 19, 4335.

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