TITLE:
A Multi-Agent Approach to Arabic Handwritten Text Segmentation
AUTHORS:
Ashraf Elnagar, Rahima Bentrcia
KEYWORDS:
Character Segmentation; Handwritten Recognition Systems; Multi-Agents; Arabic Handwriting
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.4 No.3,
August
30,
2012
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%.