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A novel hyperspectral camera and analysis platform for the non-destructive material identification and mapping: an application in paintings by El Greco

Balas Costas, Epitropou Georgios, Tsapras Athanasios, Hadjinicolaou, Nicos, 1938-

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/A508C5FD-A4FC-4B46-ACF7-3426F90DA35F
Έτος 2016
Τύπος Πλήρης Δημοσίευση σε Συνέδριο
Άδεια Χρήσης
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Βιβλιογραφική Αναφορά C. Balas, G. Epitropou, A. Tsapras and N. Hadjinicolaou, "A novel hyperspectral camera and analysis platform for the non-destructive material identification and mapping: an application in paintings by El Greco," in IEEE International Conference on Imaging Systems and Techniques, 2016, pp. 211-215. doi: 10.1109/IST.2016.7738225 https://doi.org/10.1109/IST.2016.7738225
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Περίληψη

Non-destructive point spectroscopic techniques and destructive methods based on sampling and ex-situ analysis are not efficient for examining large areas of objects of artistic and historic value. A novel hyperspectral camera and analysis platform (HySCAP) is presented in this paper, integrating innovative electrooptic solutions and advanced spectral analysis and classification algorithms. This combination offers and attractive alternative to a variety of destructive or ionizing methods used routinely for material identification. HySCAP acquires millions of reflectance and/or fluorescence spectra and tens of narrow band images, spanning the entire 370nm-1100nm wide spectral range. Specially developed and integrated into the HySCAP spectral analysis and system's training tools maximizes the obtained information with regard to the target-object's composition and structure. We have validated the HySCAP concept in a series of painting material replicas and in paintings belonging to El Greco's workshop, made by either the master himself or his students. Painting material replicas were developed following the original development processes and their fluorescence and reflectance spectra were measured and stored in the HySCAP's database. Some of them were used as training set and some other as validation set. The properly designed spectral analysis module was employed for handling the automated comparison of the training set of spectra with the spectra collected from the validation set of samples. Particularly, a series of algorithms for performing spectral comparison and classification were comparatively evaluated. It was found that the best performing algorithm was the Maximum Likelihood algorithm, which displayed accuracies within the range 80.3%-99.7% in identifying and mapping materials in El Greco's workshop paintings. The obtained results indicate that the HySCAP integrated approach emerges as a valuable scientific instrument for developing a series of more efficient methods in the broad field of nondestructive testing. In the particular case of the artwork analysis, which is presented in this paper, the offered new insight into the material composition, technique of construction, deterioration effects, authentication etc., are of essential importance in art history, in authentication and in determining the optimum preservation scheme.

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