In the forensic examination of automotive paint, each layer of paint is analyzed individually by infrared (IR) spectroscopy. Laboratories in North America typically hand section each layer and present each separated layer to an IR spectrometer for analysis, which is time consuming. In addition, sampling too close to the boundary between adjacent layers can pose a problem as it produces an IR spectrum that is a mixture of two layers. Not having a “pure” IR spectrum of each layer will prevent a meaningful comparison between each paint layer or in the situation of searching an automotive database will prevent the forensic paint examiner from developing an accurate hit list of potential suspects. These two problems have been addressed by collecting concatenated IR data from all paint layers in a single analysis by interrogating the cross sectioned layers of the paint sample using Fourier transform infrared (FTIR) imaging microscopy. Using an ultramicrotome instead of a conventional microtome allows for so-called “small” paint chips which are often found on the clothing of a pedestrian in a hit-and-run to be cross sectioned and analyzed than what is practical by conventional FTIR. Decatenation of the concatenated IR data is achieved by multivariate curve resolution using alternating least squares (ALS) or modified alternating least squares (MALS) to obtain an IR spectrum of each automotive paint layer. A new baseline correction algorithm that integrates three well known baseline correction methods developed a snapshot of the background and minimized error in the MALS recovered spectra. In addition, limiting the FTIR spectrum of each layer to the region corresponding to the binder is shown to be sufficient to identify the assembly plant of the automotive vehicle and perform accurate library searches to identify the vehicle manufacturer, line, and model of the vehicle from which the original equipment manufacturer paint chip originated.