Abstract:
: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.
journal_name
Forensic Sci Intjournal_title
Forensic science internationalauthors
Thoonen G,Nys B,Vander Haeghen Y,De Roy G,Scheunders Pdoi
10.1016/j.forsciint.2015.12.040subject
Has Abstractpub_date
2016-02-01 00:00:00pages
210-20eissn
0379-0738issn
1872-6283pii
S0379-0738(15)00541-1journal_volume
259pub_type
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