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A Multi-Agent Approach to Arabic Handwritten Text Segmentation
Computer Science Department, College of Sciences, University of Sharjah, Sharjah, UAE.
Computer Science Department, College of Sciences, University of Sharjah, Sharjah, UAE.
- 1 Computer Science Department, College of Sciences, University of Sharjah, Sharjah, UAE.
- 2 Computer Science Department, College of Sciences, University of Sharjah, Sharjah, UAE.
Journal of Intelligent Learning Systems and Applications·Volume 04 (2012)·Pages 207–215·Published 30 August 2012·DOI10.4236/jilsa.2012.43021
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Abstract
The segmentation of individual words into characters is a vital process in handwritten character recognition systems. In this paper, a novel approach is proposed to segment handwritten Arabic text (words). We consider the “Naskh” font style. The segmentation algorithm employs seven agents in order to detect regions where segmentation is illegal. Feature points (end points) are extracted from the remaining regions of the word-image. Initially, the middle of every two successive end points is considered as a candidate segmentation point based on a set of rules. The experimental results are very promising as we achieved a success rate of 86%.
KeywordsCharacter SegmentationHandwritten Recognition SystemsMulti-AgentsArabic Handwriting
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