A novel classification method for multispectral imaging combined with portable Raman spectroscopy for the analysis of a painting by vincent van gogh

In this work, a novel combination of portable micro-Raman spectroscopy and semi-automatic methods of data treatment are proposed for the classification and mapping of visible multispectral imaging data for the analysis of a painting on paper by Vincent Van Gogh. Analysis of multispectral imaging data with the sequential maximum-angle convex cone (SMACC) and spectral angle mapper (SAM) algorithms differentiated the surface into areas on the basis of the presence of pigment mixtures. Complementary analytical information was obtained through portable Raman spectroscopy was performed on a few selected points of the painting, allowing for the determination of Van Gogh's palette and the mapping of pigment mixtures on the painting's surface; the number of mixtures employed is varied and at least two different blues are present. The results obtained were integrated with the information from prior ultraviolet (UV)-induced luminescence analysis performed on the same painting to better understand the materials used by the artist. The mathematical treatment of multispectral data using the proposed methods could be extended to the analysis of other painted surfaces