We present a scanning device for multi-spectral imaging of paintings in the 380-2300 nm spectral range (32 VIS + 14 NIR bands). The system is based on contact-less and single-point measurement of the spectral reflectance factor. Multi-spectral images are obtained by scanning the painted surface under investigation. At present the VIS and NIR modules work separately due to the lack of synchronization between them. Measurement campaigns were carried out on several paintings in situ and at the INOA Optical Metrology Laboratory located inside the Opificio delle Pietre Dure in Florence. We report herein on the measurements carried out on a few panel and canvas paintings. Multivariate image analyses (MIA) were performed and the detected images were analyzed by means of the conventional Principal Component Analysis (PCA) and the K-Nearest-Neighbouring Cluster Analysis (KNN).

A scanning device for VIS-NIR multispectral imaging of paintings

Fontana R;Greco M;Mastroianni M;Materazzi M;Pampaloni E;Pezzati L;Bencini D
2008

Abstract

We present a scanning device for multi-spectral imaging of paintings in the 380-2300 nm spectral range (32 VIS + 14 NIR bands). The system is based on contact-less and single-point measurement of the spectral reflectance factor. Multi-spectral images are obtained by scanning the painted surface under investigation. At present the VIS and NIR modules work separately due to the lack of synchronization between them. Measurement campaigns were carried out on several paintings in situ and at the INOA Optical Metrology Laboratory located inside the Opificio delle Pietre Dure in Florence. We report herein on the measurements carried out on a few panel and canvas paintings. Multivariate image analyses (MIA) were performed and the detected images were analyzed by means of the conventional Principal Component Analysis (PCA) and the K-Nearest-Neighbouring Cluster Analysis (KNN).
2008
Istituto Nazionale di Ottica - INO
Multi-spectral imaging
spectral reflectance factor
principal component analysis
multivariate image analysis
Cluster Analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/158010
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