Title
Automatic forensic analysis of automotive paints using optical microscopy
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
article
Publication
Lausanne ,
Subject
Physics
Human medicine
Source (journal)
Forensic science international. - Lausanne
Volume/pages
259(2016) , p. 210-220
ISSN
0379-0738
ISI
000369235000036
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
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.
E-info
https://repository.uantwerpen.be/docman/iruaauth/b16506/130353.pdf
Full text (open access)
https://repository.uantwerpen.be/docman/irua/c34bcf/130353.pdf
E-info
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000369235000036&DestLinkType=RelatedRecords&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000369235000036&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000369235000036&DestLinkType=CitingArticles&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
Handle