JILSA  Vol.4 No.3 , August 2012
A Multi-Agent Approach to Arabic Handwritten Text Segmentation
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 . 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%.

Cite this paper
A. Elnagar and R. Bentrcia, "A Multi-Agent Approach to Arabic Handwritten Text Segmentation," Journal of Intelligent Learning Systems and Applications, Vol. 4 No. 3, 2012, pp. 207-215. doi: 10.4236/jilsa.2012.43021.
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