Department of Chemistry, Oklahoma State University, Stillwater, OK 74078, United States.
Department of Chemistry, Oklahoma State University, Stillwater, OK 74078, United States.
Talanta. 2015 Jan;132:182-90. doi: 10.1016/j.talanta.2014.08.061. Epub 2014 Sep 3.
Clear coat searches of the infrared (IR) spectral library of the paint data query (PDQ) forensic database often generate an unusable number of hits that span multiple manufacturers, assembly plants, and years. To improve the accuracy of the hit list, pattern recognition methods have been used to develop search prefilters (i.e., principal component models) that differentiate between similar but non-identical IR spectra of clear coats on the basis of manufacturer (e.g., General Motors, Ford, Chrysler) or assembly plant. A two step procedure to develop these search prefilters was employed. First, the discrete wavelet transform was used to decompose each IR spectrum into wavelet coefficients to enhance subtle but significant features in the spectral data. Second, a genetic algorithm for IR spectral pattern recognition was employed to identify wavelet coefficients characteristic of the manufacturer or assembly plant of the vehicle. Even in challenging trials where the paint samples evaluated were all from the same manufacturer (General Motors) within a limited production year range (2000-2006), the respective assembly plant of the vehicle was correctly identified. Search prefilters to identify assembly plants were successfully validated using 10 blind samples provided by the Royal Canadian Mounted Police (RCMP) as part of a study to populate PDQ to current production years, whereas the search prefilter to discriminate among automobile manufacturers was successfully validated using IR spectra obtained directly from the PDQ database.
对油漆数据查询 (PDQ) 取证数据库的红外 (IR) 光谱库进行清漆搜索时，通常会生成大量无用的命中结果，这些结果涵盖了多个制造商、装配厂和年份。为了提高命中列表的准确性，已经使用模式识别方法来开发搜索预滤波器（即主成分模型），这些预滤波器基于制造商（例如通用汽车、福特、克莱斯勒）或装配厂来区分清漆的相似但不相同的 IR 光谱。采用两步程序来开发这些搜索预滤波器。首先，使用离散小波变换将每个 IR 光谱分解为小波系数，以增强光谱数据中的细微但重要的特征。其次，采用用于 IR 光谱模式识别的遗传算法来识别与车辆制造商或装配厂相关的小波系数。即使在具有挑战性的试验中，评估的油漆样本均来自同一制造商（通用汽车）且在有限的生产年份范围内（2000-2006 年），车辆的相应装配厂也能被正确识别。用于识别装配厂的搜索预滤波器已成功使用皇家骑警（RCMP）提供的 10 个盲样进行验证，作为将 PDQ 填充到当前生产年份的研究的一部分，而用于区分汽车制造商的搜索预滤波器则使用直接从 PDQ 数据库获得的 IR 光谱进行了成功验证。
