Pattern recognition techniques have been developed to search the infrared (IR) spectral libraries of the paint data query (PDQ) database to differentiate between similar paint spectra. The library search system consists of two separate but interrelated components: search prefilters to reduce the size of the IR library to a specific assembly plant or assembly plants corresponding to the unknown paint sample and a cross-correlation library searching algorithm to identify IR spectra most similar to the unknown in the subset of IR spectra identified by the search prefilters. Search prefilters have been developed from individual or multiple automotive paint layers. To develop search prefilters with the necessary degree of accuracy, the IR spectra are first preprocessed using wavelets to enhance subtle but significant features in the data. Wavelet coefficients characteristic of the assembly plant of the vehicle are identified using a genetic algorithm for pattern recognition analysis and feature selection. A search algorithm is then employed to cross-correlate the unknown with each IR spectrum in the subset of library spectra identified by the search prefilters. Each cross-correlated IR spectrum is simultaneously compared to an autocorrelated IR spectrum of the unknown or each spectrum in the truncated library using several spectral windows that span different regions of the cross-correlated and autocorrelated data from the midpoint. The top 5 hits identified in each search window are compiled and a histogram is computed that summarizes the frequency of occurrence for each selected library sample. The 5 library samples with the highest frequency of occurrence are selected as potential hits. Even in challenging trials where the paint samples evaluated were all the same make (e.g., General Motors, Chrysler or Ford) within a limited production year range, the model of the automobile from which the unknown paint sample was obtained could be identified from its IR spectrum. To assess the quality of these matches, several approaches have been implemented including likelihood ratios.

Pattern recognition assisted infrared library searching of automotive paints for forensic analysis

251st National Meeting (2016)

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