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Improving PDQ Database Search Strategies To Enhance Investigative Lead Information for Automotive Paints

NCJ Number
249426
Author(s)
S.K. Lavine, A. Fasasi, M. Sandercock
Date Published
November 2014
Length
5 pages
Annotation
Applying low level data fusion techniques where spectra from multiple sources (e.g., IR spectra of clear coat and primer paint layers) are combined and class membership information is extracted, search prefilters have been developed to determine the assembly plant of the vehicle from which an unknown paint sample originated.
Abstract
Modern automotive paints have a thin clear coat which on a microscopic fragment is often too thin to obtain accurate chemical information. The small size of the fragment also makes it difficult to accurately compare it with the manufacturer's paint color standards. Because adhesion between paint layers is usually very strong, both primer layers are often transferred during a collision if the clear coat and color coat layers are also transferred. The application of low-level fusion techniques, however, found that even in challenging trials where the clear coat and undercoat layers evaluated were all from the same make (General Motors) within a limited production year range, the respective assembly plants of the vehicles could be identified using only chemical information. The development of search prefilters for the PDQ database to exploit multiple sources of IR data is needed to extract investigative lead information from clear coat and primer paint layer smears. (Publisher abstract modified)
Date Published: November 1, 2014