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Offline Arabic handwriting recognition: a survey.

Liana M Lorigo1, Venu Govindaraju

  • 1Department of Computer Science and Engineering, State University of New York at Buffalo, Amherst 14228, USA. lmlorigo@buffalo.edu

IEEE Transactions on Pattern Analysis and Machine Intelligence
|April 28, 2006
PubMed
Summary
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This paper reviews methods for Arabic handwriting recognition, a challenging field. It offers a comprehensive survey of techniques and future research directions for this specialized area.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Pattern Recognition

Background:

  • Automatic text recognition from images has numerous applications.
  • Arabic handwriting recognition presents unique challenges and is a developing research area.
  • Existing methods for Arabic handwriting recognition vary widely.

Purpose of the Study:

  • To provide a comprehensive review of methods for Arabic handwriting recognition.
  • To be the first survey focused specifically on Arabic handwriting recognition.
  • To offer recognition rates and test data descriptions for discussed approaches.

Main Methods:

  • Literature review of existing Arabic handwriting recognition techniques.
  • Categorization and analysis of different proposed methods.

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  • Discussion of challenges and future research directions.

    • Main Results:

    • Identified a variety of methods applied to Arabic handwriting recognition.
    • Highlighted the novelty of this survey as the first to focus on Arabic handwriting.
    • Provided comparative data on recognition rates and test datasets.

    Conclusions:

    • Arabic handwriting recognition is a complex but advancing field.
    • A comprehensive understanding of current methods is crucial for future progress.
    • Further research is needed to overcome existing challenges and improve recognition accuracy.