T. Sari and M. Sellami
Arabic character segmentation and recognition, neural nets, smoothing, contour following, contour filling, rule based system
Character segmentation is a necessary preprocessing step for character recognition in many OCR systems. It is an important step because incorrectly segmented characters will not be recognized correctly. The most difficult case in character segmentation is cursive script. The scripted nature of Arabic written language poses some high challenges for automatic character segmentation and recognition. The authors present a new Character Segmentation Algorithm (ACSA) of Arabic script. The developed segmentation algorithm yields the splitting up of isolated handwritten words in perfectly separated characters. It is based on topological rules, which are constructed at the feature extraction phase. To increase ACSA’s performances, it was combined it with an Arabic characters recognition system, RECAM.
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