Abstract

Mid-infrared fiber-optics reflectance spectroscopy supported by classification procedures based on the Mahalanobis distance in the principal component space was applied to investigate laboratory samples simulating actual paintings. The spectral data obtained were analyzed by means of principal component analysis (PCA). The application of PCA to first-derivative spectra resulted as a robust method of processing spectral data and made it possible to distinguish the binding medium and/or the pigment/dye, and to classify test samples by means of the Mahalanobis distance discrimination method.

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Intra-class variability in diffuse reflectance spectroscopy: application to porcine adipose tissue

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Comparison of a physical model and principal component analysis for the diagnosis of epithelial neoplasias in vivo using diffuse reflectance spectroscopy

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Infrared Reflectance of Paints

Arthur B. Krewinghaus
Appl. Opt. 8(4) 807-812 (1969)

Fluorescence spectral imaging for characterization of tissue based on multivariate statistical analysis

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