Visual Recognition of Arabic Handwriting: Challenges and New Directions

  • Mohamed Cheriet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4768)


Automatic recognition of Arabic handwritten text presents a problem worth solving; it has increasingly more interest, especially in recent years. In this paper, we address the most frequently encountered problems when dealing with Arabic handwriting recognition, and we briefly present some lessons learned from several serious attempts. We show why morphological analysis of Arabic handwriting could improve the accuracy of Arabic handwriting recognition. In general, Arabic Natural Language Processing could provide some error handling techniques that could be used effectively to improve the overall accuracy during post-processing. We give a summary of techniques concerning Arabic handwriting recognition research. We conclude with a case study about the recognition of Tunisian city names, and place emphasis on visual-based strategies for Arabic Handwriting Recognition (AHR).


Hide Markov Model Natural Language Processing Visual Recognition Word Class Arabic Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Mohamed Cheriet
    • 1
  1. 1.Laboratory for Imagery, Vision and Artificial IntelligenceÉcole de Technologie Supérieure (University of Quebec)MontrealCanada

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