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Conference Papers Year : 2006

Online Arabic Handwriting Recognition Using Hidden Markov Models

Fadi Biadsy
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Jihad El-Sana
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Nizar Habash
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  • PersonId : 836109


Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. This paper introduces a Hidden Markov Model (HMM) based system to provide solutions for most of the difficulties inherent in recognizing Arabic script including: letter connectivity, position-dependent letter shaping, and delayed strokes. This is the first HMM-based solution to online Arabic handwriting recognition. We report successful results for writerdependent and writer-independent word recognition.
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inria-00108306 , version 1 (20-10-2006)


  • HAL Id : inria-00108306 , version 1


Fadi Biadsy, Jihad El-Sana, Nizar Habash. Online Arabic Handwriting Recognition Using Hidden Markov Models. Tenth International Workshop on Frontiers in Handwriting Recognition, Université de Rennes 1, Oct 2006, La Baule (France). ⟨inria-00108306⟩


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