Extended Feature Extraction Technique (Edge Direction Matrixes) For Online Arabic Handwriting Recognition

Mohamed Mosadag Albadawi, Hozeifa Adam Abd Alshafy


Recognition of Arabic handwriting has attracted the interest of researchers for many years. Until now it has been a challenging research area due to many issues. The feature extraction is an essential stage in the recognition systems of handwriting. The main idea behind this paper is to study EDMs (Edge Direction Matrixes) as a feature extraction technique for Online Arabic Handwriting Recognition. In this study, SUSTOLAH datasets will be used, in which datasets of online Arabic handwriting are presented in Sudan University of Science and Technology. In this paper, satisfactory results have been achieved, where the value of the correlation/regress coefficient for the differences between the variant handwritten characters is found to be -0.01322.


On-line Arabic handwriting, feature extraction, edge direction matrixes (EDMS).

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