On Line Recognition System for Arabic Handwritten Text | ||
| International Conference on Aerospace Sciences and Aviation Technology | ||
| Article 81, Volume 10, 10th International Conference On Aerospace Sciences & Aviation Technology, May 2003, Pages 1147-1158 PDF (2.22 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/asat.2013.24743 | ||
| Authors | ||
| M. Shaarawy1; Aly Fahmy2; M. M. Fouad1 | ||
| 1Egyptian Armed Forces. | ||
| 2Faculty of Infonnation & Computers, Cairo University, Egypt. | ||
| Abstract | ||
| This paper presents the design and the implementation of an On Line Arabic text Recognition system "OLAR" that is used for cursive handwritten recognition. In addition to Arabic characters, OLAR can recognize numerical characters, and special symbols. The direction and style of writing are used to compose the main components of the feature vector of the characters to be recognized. OLAR uses Euclidean distance approach and artificial neural networks for classification. The obtained results showed that OLAR can compete well with other handwriting recognition systems. The recognition rate ranges from 90% to 100%. | ||
| Keywords | ||
| Arabic Text Recognition; Artificial Neural Networks; Handwritten Text Recognition | ||
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