Abstract
Problem statement: Arabic offline handwriting recognition is considered one of the most challenging topics. This is probably caused by the fact that Arabic recognition system faced many problems during the development stage. It faces the usual problems of character recognition in general, in addition to the problems that are specific to Arabic language only. The aim of this study was to build a classifier to solve Arabic text ambiguity; to be used in text recognition applications. Approach: A multilevel classifier based on pattern recognition techniques, is proposed. The proposed classifier was implemented using MATLAB and also tested with a large sample of handwritten datasets. Results: Pattern recognition techniques are used to identify Arabic handwritten text. After testing, the recognition rates reached {93, 84, 89 and 85%} for the isolated letters, letters at the beginning, at the middle and at the end of the word respectively. Conclusion: Even that the Arabic letters change their shape depending on their position in a word, the proposed classifier, using the powerful set of features, is proved to be effective in the recognition of Arabic letters.
Highlights
IntroductionA system which permits rapid and accurate correction of rejects is a major requirement
Character recognition systems have never achieved a read rate that is 100%
The researchers dealing with processing of unconstrained secondary parts a set of features were detected handwritten Arabic cursive scripts must overcome such as the number and type of secondary parts, the many difficulties such as unlimited variation in human handwriting, similarities of distinct character shapes, character overlaps and interconnections of neighboring characters (Abandah et al, 2009)
Summary
A system which permits rapid and accurate correction of rejects is a major requirement. The success of any Optical Recognition System (OCR) device to read accurately without substitutions is not the sole responsibility of the hardware manufacturer. Much depends on the quality of the items to be processed. The desire has been to increase the accuracy of reading, that is, to reduce rejects and substitutions, to reduce the sensitivity of scanning to read less-controlled input, to eliminate the need for specially designed fonts (characters) and to read handwritten characters (online/offline) (Ergin et al, 2010). Arabic language has its own features that affect the recognition process of the Arabic letters.
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