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Title: Writer identification by means of explainable features: shapes of loops and lead-in strokes
Author(s): Blankers, V.L.; Niels, R.M.J. ; Vuurpijl, L.G.
Publication year: 2007
In: BNAIC'07: Proceedings of the 19th Belgium-Netherlands Artificial Intelligence Conference 2007, pp. 17-24
Publisher: [S.l. : s.n.]
Publication type: Article in monograph or in proceedings

Please use this identifier to cite or link to this item : http://hdl.handle.net/2066/55893   http://hdl.handle.net/2066/55893

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Subject: Cognitive artificial intelligence
DI-BCB_DCC_Theme 4: Brain Networks and Neuronal Communication
Organization: SW OZ DCC KI
Former Organization: SW OZ NICI KI
Book title: BNAIC'07: Proceedings of the 19th Belgium-Netherlands Artificial Intelligence Conference 2007
Issue: iss. BNAIC ; 19
Page start: p. 17
Page end: p. 24
Abstract:
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.

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