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Exploiting Character Class Information in Forensic Writer Identification
Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain. (ATVS/Biometric Recognition Group)ORCID iD: 0000-0002-1400-346X
Universidad Autonoma de Madrid, Spain.
Universidad Autonoma de Madrid, Spain.
Universidad Autonoma de Madrid, Spain.
2011 (English)In: Computational forensics: 4th International Workshop, IWCF 2010 Tokyo, Japan, November 11-12, 2010 : revised selected papers, Berlin: Springer Berlin/Heidelberg, 2011, 31-42 p.Conference paper (Refereed)
Abstract [en]

Questioned document examination is extensively used by forensic specialists for criminal identification. This paper presents a writer recognition system based on contour features operating in identification mode (one-to-many) and working at the level of isolated characters. Individual characters of a writer are manually segmented and labeled by an expert as pertaining to one of 62 alphanumeric classes (10 numbers and 52 letters, including lowercase and uppercase letters), being the particular setup used by the forensic laboratory participating in this work. Three different scenarios for identity modeling are proposed, making use to a different degree of the class information provided by the alphanumeric samples. Results obtained on a database of 30 writers from real forensic documents show that the character class information given by the manual analysis provides a valuable source of improvement, justifying the significant amount of time spent in manual segmentation and labeling by the forensic specialist. © 2011 Springer-Verlag Berlin Heidelberg.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2011. 31-42 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 6540
National Category
Signal Processing
URN: urn:nbn:se:hh:diva-21232DOI: 10.1007/978-3-642-19376-7_3ISI: 000296680900003ScopusID: 2-s2.0-79952259378ISBN: 978-364219375-0OAI: diva2:589360
4th International Workshop on Computational Forensics, IWCF 2010, Tokyo, Japan, 11-12 November, 2010
Available from: 2013-01-17 Created: 2013-01-17 Last updated: 2015-09-29Bibliographically approved

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Alonso-Fernandez, Fernando
Signal Processing

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