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Title: Writer identification through information retrieval: the allograph weight vector
Author(s): Niels, R.M.J. ; Grootjen, F.A. ; Vuurpijl, L.G.
Publication year: 2008
In: 11th International Conference on the Frontiers of Handwriting Recognition (ICFHR.2008), pp. 481-486
Publisher: Montreal, Canada : Concordia Univ
Publication type: Article in monograph or in proceedings

Please use this identifier to cite or link to this item : https://hdl.handle.net/2066/73284   https://hdl.handle.net/2066/73284

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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: 11th International Conference on the Frontiers of Handwriting Recognition (ICFHR.2008)
Page start: p. 481
Page end: p. 486
Abstract:
We show a number of promising results in writer identification, by recasting the traditional information retrieval (IR) problem of finding documents based on the frequency of occurrence of their terms. In IR, the tf-idf is a well-known statistical measure that weighs the importance of certain terms occurring in a database of documents. Here, writers are searched on the basis of the frequency of occurrence of particular character shapes: the allographs. The results show a high retrieval score. Moreover, by using the af-iwf (allograph frequency - inverse writer frequency) measure, qualitative and quantitative analyses can be made that elaborate on the particular allograph shapes that lead to a succesful writer identification. In this paper, we sketch the application of these techniques in forensic science

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