Lavine Barry K, White Collin G, Allen Matthew D, Weakley Andrew
1 Department of Chemistry, Oklahoma State University, Stillwater, Oklahoma, USA.
2 IMPROVE Group, Crocker Nuclear Laboratory, University of California, Davis, California, USA.
Appl Spectrosc. 2017 Mar;71(3):480-495. doi: 10.1177/0003702816666287. Epub 2016 Oct 6.
Multilayered automotive paint fragments, which are one of the most complex materials encountered in the forensic science laboratory, provide crucial links in criminal investigations and prosecutions. To determine the origin of these paint fragments, forensic automotive paint examiners have turned to the paint data query (PDQ) database, which allows the forensic examiner to compare the layer sequence and color, texture, and composition of the sample to paint systems of the original equipment manufacturer (OEM). However, modern automotive paints have a thin color coat and this layer on a microscopic fragment is often too thin to obtain accurate chemical and topcoat color information. A search engine has been developed for the infrared (IR) spectral libraries of the PDQ database in an effort to improve discrimination capability and permit quantification of discrimination power for OEM automotive paint comparisons. The similarity of IR spectra of the corresponding layers of various records for original finishes in the PDQ database often results in poor discrimination using commercial library search algorithms. A pattern recognition approach employing pre-filters and a cross-correlation library search algorithm that performs both a forward and backward search has been used to significantly improve the discrimination of IR spectra in the PDQ database and thus improve the accuracy of the search. This improvement permits inter-comparison of OEM automotive paint layer systems using the IR spectra alone. Such information can serve to quantify the discrimination power of the original automotive paint encountered in casework and further efforts to succinctly communicate trace evidence to the courts.
多层汽车漆碎片是法医学实验室中遇到的最复杂材料之一，在刑事调查和起诉中起着关键作用。为了确定这些漆碎片的来源，法医汽车漆检验人员求助于油漆数据查询（PDQ）数据库，该数据库可让法医检验人员将样本的层序、颜色、质地和成分与原始设备制造商（OEM）的漆系统进行比较。然而，现代汽车漆的色漆层很薄，而在微观碎片上的这一层往往太薄，无法获得准确的化学和面漆颜色信息。为了提高辨别能力并对OEM汽车漆比较的辨别力进行量化，已为PDQ数据库的红外（IR）光谱库开发了一种搜索引擎。PDQ数据库中原始漆层相应层的红外光谱相似性，常常导致使用商业库搜索算法时辨别效果不佳。一种采用预过滤器和互相关库搜索算法的模式识别方法，该算法可进行正向和反向搜索，已被用于显著提高PDQ数据库中红外光谱的辨别力，从而提高搜索的准确性。这种改进使得仅使用红外光谱就可以对OEM汽车漆层系统进行相互比较。这些信息可用于量化实际案件中遇到的原始汽车漆的辨别力，并进一步努力将微量证据简洁地传达给法庭。
