Automatic Identification of Artistic Pigments by Raman Spectroscopy Using Fuzzy Logic and Principal Component Analysis

This work offers an automatic identification system of Raman spectra of artistic pigments. The proposed methodology is based on a fuzzy logic system, and uses principal component analysis to reduce redundancies in data and the correlation operator as an index of similarity between two Raman spectra. Moreover, as sometimes pigments are used in mixtures by artist, the designed system is able to recognize binary mixtures of pigments on the basis of their Raman fingerprints.