Journal of Intelligent Learning Systems and Applications, 2012, 4, 207-215 http://dx.doi.org/10.4236/jilsa.2012.43021 Published Online August 2012 (http://www.SciRP.org/journal/jilsa) 1 A Multi-Agent Approach to Arabic Handwritten Text Segmentation Ashraf Elnagar * , Rahima Bentrcia Computer Science Department, College of Sciences, University of Sharjah, Sharjah, UAE. Email: * ashraf@sharjah.ac.ae Received November 24 th , 2011; revised April 19 th , 2012; accepted April 26 th , 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. Fea- ture 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 1. Introduction For the past three decades, there has been increasing in- terest among researchers in problems related to hand- written text segmentation and recognition regardless of the language used [1]. Most of the handwriting recogni- tion systems are based on segmentation, which is the operation that seeks to decompose a word image into a sequence of sub-images containing isolated characters. Despite of the extensive work done on the off-line rec- ognition of handwritten Latin and Asian languages text, a small number of research papers and reports are pub- lished in the recognition of Arabic handwriting [2]. This is probably a result of a lack of adequate support in terms of funding, and other utilities, such as comprehensive and standard Arabic text databases, dictionaries, etc.; and certainly due to difficulties associated with Arabic hand- written text segmentation such as the cursive nature of Arabic handwriting where most of the characters in a single word are connected to each other. Another diffi- culty is the existence of overlapping characters which are not attached to each other but share horizontal space. Due to difficulties mentioned above, many researchers bypass the segmentation stage in developing a recogni- tion system. However, this is not practical and insuffi- cient in applications that require recognition of a large number of vocabularies where several words may have the same global shape, such as bank check processing, postal address and zip code recognition [3,4], automated handwritten document entry and understanding, mail sort- ing, and other business and scientific applications. In addi- tion, segmentation has an effective role in reducing the complexity of recognition systems since the number of recognition classes will be the number of Arabic letters and not the possible combinations of them. In this paper, we address the problem of segmenting Arabic handwritten words into characters. The proposed approach utilizes seven agents which cooperate to iden- tify the regions where the insertion of segmentation points is illegal. The segmentation algorithm is described in Figure 1 as a block diagram. First, the image of the Figure 1. The basic steps in the algorithm. * Corresponding author. Copyright © 2012 SciRes. JILSA