Evaluation of Hyperspectral Imaging Visible/Near Infrared Spectroscopy as a forensic tool for automotive paint distinction

Abstract

Spectroscopies have been widely used in forensic science to analyze fingerprints, bloodstains, paints, etc. Hyperspectral chemical imaging is a fast and non-destructive method that provides spatial and spectral chemical information of a particular specimen. Recently, researchers have evaluated the characterization of automotive paints using Principal Components Analysis (PCA) performed on infrared and Raman spectroscopies data. However, to date, there is no report concerning the discrimination power of such trace evidence using Hyperspectral Imaging Visible/Near Infrared Spectroscopy (HSI-UV/VIS/NIR). Therefore, this work evaluated the potential of this technique combined with PCA as a forensic approach to discriminate automotive paints. In total, 38 samples from twelve brands and a variety of colors were analyzed. HSI-UV/VIS/NIR data was acquired directly from the paint chip’s surfaces, which includes the basecoat and clear coat layers. PCA was individually performed in distinct color datasets and could discriminate 100% of the white, silver, red and grey samples collected from different brands or from the same manufacturer with different color/shades. Furthermore, the PCA reliability for the identification of similar paint chips was successfully tested using fragments of silver and grey samples collected from different vehicle sources with common brand, color and shade. In agreement with the literature, the automotive black paints presented a much lower discriminating power (62.5%) because the spectra did not provide enough reflectance suitable for differentiation. These new findings support the idea of using HSI-UV/VIS/NIR as a fast, easy and efficient alternative technique to other spectroscopies for accurate forensic assessment of automotive paints.