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On-line Handwritten Arabic Character Recognition using Artificial Neural Network

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 55 - Number 13
Year of Publication: 2012
Khaoula Addakiri
Mohamed Bahaj

Khaoula Addakiri and Mohamed Bahaj. Article: On-line Handwritten Arabic Character Recognition using Artificial Neural Network. International Journal of Computer Applications 55(13):42-46, October 2012. Full text available. BibTeX

	author = {Khaoula Addakiri and Mohamed Bahaj},
	title = {Article: On-line Handwritten Arabic Character Recognition using Artificial Neural Network},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {55},
	number = {13},
	pages = {42-46},
	month = {October},
	note = {Full text available}


In this paper, an efficient approach for the recognition of on-line Arabic handwritten characters is presented. The method employed involves three phases: First, pre-processing in which the original image is transformed into a binary image . Second , training neural networks with feed-forward back propagation algorithm . Finally, the recognition of the character through the use of Neural Network techniques. The proposed approach is tested on 1400 different characters written by ten users. Each user wrote 28 Arabic characters five times in order to get different writing variations. Experiment results showed the effectiveness of our approach for recognizing handwritten Arabic characters.


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