Writer identification by means of explainable features: shapes of loops and lead-in strokes
Publication year
2007Publisher
[S.l.] : [S.n.]
In
BNAIC'07: Proceedings of the 19th Belgium-Netherlands Artificial Intelligence Conference 2007, pp. 17-24Publication type
Article in monograph or in proceedings

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Organization
SW OZ DCC AI
Former Organization
SW OZ NICI KI
Issue
iss. BNAIC ; 19
Book title
BNAIC'07: Proceedings of the 19th Belgium-Netherlands Artificial Intelligence Conference 2007
Page start
p. 17
Page end
p. 24
Subject
(ISSN 1568-7805); Cognitive artificial intelligence; DI-BCB_DCC_Theme 4: Brain Networks and Neuronal CommunicationAbstract
Writer identification is an important issue in forensic investigations of handwritten documents. A particularly
well-established method employed by forensic experts is to (visually) explore distinguishing features
of handwritten characters for comparing pieces of handwriting. Our research within the NWO Trigraph
project aims at automizing this laborious process. In this paper, we propose a novel method for identifying
a writer by means of features of loops and lead-in strokes of handwritten characters. Using a k-nearestneighbor
classifier, we were able to yield a correct identification performance of 98% on a database of 41
writers. These results are promising and have great potential for use in the forensic practice, where the
outcomes of handwritten document comparisons have to be justified via explainable features like the ones
explored in this paper.
This item appears in the following Collection(s)
- Academic publications [204968]
- Electronic publications [103219]
- Faculty of Social Sciences [27347]
- Open Access publications [71773]
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