Improving Investigative Lead Information and Evidential Significance Assessment for Automotive Paint and the PDQ Database

摘要

New pattern recognition techniques have been developed for searching infrared (IR) spectral libraries of the Paint Data Query (PDQ) automotive paint database to differentiate between similar but nonidentical Fourier transform infrared paint spectra, and to determine the assembly plant, model, and line of the vehicle from which an unknown paint sample originated. Currently, modern automotive paints use thinner undercoat and color coat layers protected by a thicker clear coat layer. As a result, a clear coat paint smear is sometimes the only layer of automotive paint left at the crime scene. In these cases, the text based portion of the PDQ database cannot identify the motor vehicle because of the reliance of the search on large variations in color and chemical formulation, which do not exist with clear coats. However, clear coat paint layers, like the undercoat and color coat paint layers, exhibit chemical features in their IR spectra indicative of the automobile manufacturing plant at which they were applied, so clear coat spectra may be used to identify the model, and line of a motor vehicle. An added advantage of using pattern recognition techniques to identify paint samples from their IR spectra will be an increase in accuracy because spectra from the entire database are searched. Information derived from these searches can serve to quantify the general discrimination power of original automotive paint comparisons encountered in casework, and will further efforts to succinctly communicate the significance of the evidence to the courts.