The effect of environmental degradation on the characterisation of automotive clear coats by infrared spectroscopy

Pal, Karin J. van der; Sauzier, Georgina; Marić, Mark; Bronswijk, Wilhelm van; Pitts, Kari; Lewis, Simon W.

doi:10.1016/j.talanta.2015.08.058

Cited by 17 publications

(3 citation statements)

References 18 publications

(45 reference statements)

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“…Marić et al also used DART-MS to classify clear coats . Van der Pal et al studied the degradation of automotive clear coats using a range of different infrared (IR) techniques and chemometrics . They determined that spectra should be taken from the middle of a clear coat to avoid encountering degraded material.…”

Section: Paintmentioning

confidence: 99%

“…65 Van der Pal et al studied the degradation of automotive clear coats using a range of different infrared (IR) techniques and chemometrics. 66 They determined that spectra should be taken from the middle of a clear coat to avoid encountering degraded material. Perera et al went further with the chemometrics and found search prefilters for clear coats in the Paint Data Query (PDQ) database with ATR FT-IR spectroscopic data.…”

Section: ■ Paintmentioning

confidence: 99%

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Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis

et al. 2018

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Section: Paintmentioning

confidence: 99%

Section: ■ Paintmentioning

confidence: 99%

Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis

et al. 2018

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“…[8][9][10][11][12][13][14] Other research groups have also applied pattern recognition techniques to IR spectra of clear coats. [15][16][17] The current study focuses on determining the identity of an automotive vehicle from an intact paint chip recovered from a crime scene. The methodology used to develop the assembly plant search pre-filters for a single automotive paint layer in the original prototype pattern recognition library search system has been modified to tackle automotive paint samples consisting of multiple layers (clear coat, surfacer-primer, and e-coat layers).…”

Section: Introductionmentioning

confidence: 99%

Pattern Recognition-Assisted Infrared Library Searching of the Paint Data Query Database to Enhance Lead Information from Automotive Paint Trace Evidence

et al. 2016

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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.

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Automatic forensic analysis of automotive paints using optical microscopy

Thoonen

Nys

Haeghen

et al. 2016

Forensic Science International

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The timely identification of vehicles involved in an accident, such as a hit-and-run situation, bears great importance in forensics. To this end, procedures have been defined for analyzing car paint samples that combine techniques such as visual analysis and Fourier transform infrared spectroscopy. This work proposes a new methodology in order to automate the visual analysis using image retrieval. Specifically, color and texture information is extracted from a microscopic image of a recovered paint sample, and this information is then compared with the same features for a database of paint types, resulting in a shortlist of candidate paints. In order to demonstrate the operation of the methodology, a test database has been set up and two retrieval experiments have been performed. The first experiment quantifies the performance of the procedure for retrieving exact matches, while the second experiment emulates the real-life situation of paint samples that experience changes in color and texture over time.

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The effect of environmental degradation on the characterisation of automotive clear coats by infrared spectroscopy

Cited by 17 publications

References 18 publications

Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis

Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis

Pattern Recognition-Assisted Infrared Library Searching of the Paint Data Query Database to Enhance Lead Information from Automotive Paint Trace Evidence

Automatic forensic analysis of automotive paints using optical microscopy

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