Abstract
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.
Cite
CITATION STYLE
Addakiri, K., & Bahaj, M. (2012). On-line Handwritten Arabic Character Recognition using Artificial Neural Network. International Journal of Computer Applications, 55(13), 42–46. https://doi.org/10.5120/8819-2819
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