Handwritten Arabic character recognition: which feature extraction method?

Lawgali, Ahmed, Bouridane, Ahmed, Angelova, Maia and Ghassemlooy, Zabih (2011) Handwritten Arabic character recognition: which feature extraction method? International Journal of Advanced Science and Technology, 34. pp. 1-8. ISSN 2005-4238

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Abstract

Recognition of Arabic handwriting characters is a difficult task due to similar appearance of some different characters. However, the selection of the method for feature extraction remains the most important step for achieving high recognition accuracy. The purpose of this paper is to compare the effectiveness of Discrete Cosine Transform and Discrete Wavelet transform to capture discriminative features of Arabic handwritten characters. A new database containing 5600 characters covering all shapes of Arabic handwriting characters has also developed for the purpose of the analysis. The coefficients of both techniques have been used for classification based on a Artificial Neural Network implementation. The results have been analysed and the finding have demonstrated that a Discrete Cosine Transform based feature extraction yields a superior recognition than its counterpart.

Item Type: Article
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer Science and Digital Technologies
Related URLs:
Depositing User: EPrint Services
Date Deposited: 07 Oct 2011 12:34
Last Modified: 08 May 2017 22:07
URI: http://nrl.northumbria.ac.uk/id/eprint/1908

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