HYPERSPECTRAL IMAGING APPLIED TO DIAGNOSTICS AND CONSERVATION: A METHODOLOGICAL APPROACH FOR PICTORIAL LAYER CHARACTERIZATION

The use of Hyper-Spectral Imaging (HSI) as a diagnostic tool in the field of cultural heritage is of great interest presenting high potentialities, being non-destructive, non-invasive and portable. The obtained 2D information (i.e. one spectrum for each pixel of the target image) can be thus used to characterize, map and monitor the materials constituting and artefacts of cultural interest. Such noninvasive diagnostic technique can be applied by mobile devices directly in situ. The adoption of HSI techniques allows the acquisition of the spectra without a direct physical contact and/or sampling of material objects under investigations. This research is addressed to the development of a methodology to classify different pigments through HSI. Reference samples were prepared using 6 pigments (i.e. red ocher, yellow ocher, yellow chrome, blue mineral, cobalt green, and malachite) mixed with four binders (i.e arabic gum, gouache, egg tempera and oil). The obtained products were then applied on two different supports (i.e. canvas and wood) in order to obtain different combinations of pigment/support. The spectral changes of each pigment, according to the different supports, were preliminary evaluated with reference to the spectrum of the original powder pigment. The study was then addressed to verify, according to the information acquired in the different wavelength regions, the correlation existing between collected spectral signatures and sample characteristics related to the different utilized pigments, binders and supports. The resulting reference samples were acquired by HSI in the SWIR (1000-2500 nm) wavelength range. Data were processed adopting a chemometric approach based on the PLS_Toolbox (Version 7.8, Eigenvector Research, Inc.) running inside Matlab® (Version 7.5, The Mathworks, Inc.). The following chemometric methods were applied: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square- Discriminant Analysis (PLS-DA) to build classification models. Results showed as it is possible to identify a pigment on the surface of painting using a reference database built according to the collected powder pigments spectra. The developed procedures also allowed to obtain information on the utilized binder and the support.