Segmentation of Arabic Characters: A Comprehensive Survey

Ahmed M. Zeki, Mohamad S. Zakaria and Choong-Yeun Liong
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Ahmed M. Zeki: University of Bahrain, Bahrain
Mohamad S. Zakaria: Universiti Kebangsaan Malaysia, Malaysia
Choong-Yeun Liong: Universiti Kebangsaan Malaysia, Malaysia

International Journal of Technology Diffusion (IJTD), 2011, vol. 2, issue 4, 48-82

Abstract: The cursive nature of Arabic writing is the main challenge to Arabic Optical Character Recognition developer. Methods to segment Arabic words into characters have been proposed. This paper provides a comprehensive review of the methods proposed by researchers to segment Arabic characters. The segmentation methods are categorized into nine different methods based on techniques used. The advantages and drawbacks of each are presented and discussed. Most researchers did not report the segmentation accuracy in their research; instead, they reported the overall recognition rate which did not reflect the influence of each sub-stage on the final recognition rate. The size of the training/testing data was not large enough to be generalized. The field of Arabic Character Recognition needs a standard set of test documents in both image and character formats, together with the ground truth and a set of performance evaluation tools, which would enable comparing the performance of different algorithms. As each method has its strengths, a hybrid segmentation approach is a promising method. The paper concludes that there is still no perfect segmentation method for ACR and much opportunity for research in this area.

Date: 2011
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