Visual Recognition of Arabic Handwriting: Challenges and New Directions
Identifieur interne : 000B61 ( Main/Merge ); précédent : 000B60; suivant : 000B62Visual Recognition of Arabic Handwriting: Challenges and New Directions
Auteurs : Mohamed Cheriet [Canada]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2008.
Abstract
Abstract: 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).
Url:
DOI: 10.1007/978-3-540-78199-8_1
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<front><div type="abstract" xml:lang="en">Abstract: 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).</div>
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