A Multi-Agent Approach to Arabic Handwritten Text Segmentation

Ashraf Elnagar, Rahima Bentrcia

Computer Science Department, College of Sciences, University of Sharjah, Sharjah, UAE..

DOI: 10.4236/jilsa.2012.43021                

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%.

Keywords

Character Segmentation; Handwritten Recognition Systems; Multi-Agents; Arabic Handwriting

Conflicts of Interest

The authors declare no conflicts of interest.

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