Classification of heterogeneous solids using infrared hyperspectral imaging.

Methods were explored for the classification of heterogeneous powder mixtures using Fourier transform infrared (FT-IR) hyperspectral image data. The images collected were non-congruent, meaning that samples of the same mixture do not have the same spatial arrangements of their components in their images. In order to classify such images on a one-image-per-object basis, dimension reduction was carried out so as to produce a score or feature vector for each image that preserved information about the heterogeneity of the sample.