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Proceedings Paper

Improvement of Arabic handwriting recognition systems; combination and/or reject?
Author(s): Haikal El Abed; Volker Märgner
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Paper Abstract

In this paper, we present a comparison between two different combination schemes for the improvement of the performance of Arabic handwriting recognition systems. Several recognition systems (here considered as black box systems) are used from the participating systems of the Arabic handwriting recognition competition at ICDAR 2007. The outputs of these systems provide the input of our combination schemes. The first combination schemes are based on fixed fusion using logical rules, while the second one are based on trainable rules. After the normalization step of the recognition confidences and the combination of the outputs, the improvement is evaluated in term of recognition rates of a multi-classifier system with or without reject. The participating systems use the sets a to e of the IfN/ENIT database for training, and we use the set f for tests. Applying the combination rules, the results show a high recognition rate of about 95% without reject, which corresponds to an improvement of recognition rates between 8% and 15% compared to results at the ICDAR 2007 competition.

Paper Details

Date Published: 19 January 2009
PDF: 10 pages
Proc. SPIE 7247, Document Recognition and Retrieval XVI, 72470A (19 January 2009); doi: 10.1117/12.806178
Show Author Affiliations
Haikal El Abed, Technical Univ. Braunschweig (Germany)
Volker Märgner, Technical Univ. Braunschweig (Germany)


Published in SPIE Proceedings Vol. 7247:
Document Recognition and Retrieval XVI
Kathrin Berkner; Laurence Likforman-Sulem, Editor(s)

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