New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

Details

Serval ID
serval:BIB_4A49375A1C4D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC
Journal
Forensic Science International
Author(s)
Neumann C., Margot P.
Publication state
Published
Issued date
03/2009
Peer-reviewed
Oui
Volume
185
Number
1-3
Pages
38-50
Language
english
Abstract
In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context.
This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks.
Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.
Keywords
Ink evidence , Automatic comparison , Pattern recognition , Neural network
Create date
25/02/2009 12:18
Last modification date
20/08/2019 14:57
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