Recognition of Handwritten Cursive Arabic Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Compact Graph Model of Handwritten Images: Integration into Authentification and Recognition
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Persian on-line handwritten character recognition by RCE spatio-temporal neural network
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Handwritten Arabic character recognition using multiple classifiers based on letter form
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Visual recognition of Arabic handwriting: challenges and new directions
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Online handwriting recognition for the Arabic letter set
CIT'11 Proceedings of the 5th WSEAS international conference on Communications and information technology
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Arabic characters are always in cursive script. Handwritten words were entered into an IBM PC via a graphics tablet and a segmentation process applied to the points; the length and the slope of each segment was then found, and the slope categorized into one of four directions. In the learning process, specifications on the strokes of each character are fed to the computer. In the recognition process, the parameters of each stroke are found and special rules applied to select the collection of strokes which best matches the features of one of the stored characters. The results are promising, and suggestions for improvements leading to 100% recognition are proposed.