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Proceedings Paper

Segmentation versus segmentation-free for recognizing Arabic text
Author(s): May Allam
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Paper Abstract

Arabic character recognition faces many technical difficulties, but the most challenging problem is the cursive characteristic of Arabic text. The present work explores two different approaches to solve the cursive problem. The first approach depends upon preprocessing to segment connected characters. The other approach is a segmentation-free technique where whole portions of connected characters are recognized without prior segmentation. Both methods employ hidden Markov models for classification. The present paper investigates the robustness of the two techniques and suggests how to combine them so that the weakness of one is compensated for by the strength of the other.

Paper Details

Date Published: 30 March 1995
PDF: 8 pages
Proc. SPIE 2422, Document Recognition II, (30 March 1995); doi: 10.1117/12.205825
Show Author Affiliations
May Allam, Cairo Univ. (Egypt)

Published in SPIE Proceedings Vol. 2422:
Document Recognition II
Luc M. Vincent; Henry S. Baird, Editor(s)

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