A new algorithm for machine printed Arabic character segmentation
Pattern Recognition Letters
Segmentation and Pre-Recognition of Arabic Handwriting
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of off-line printed Arabic text using Hidden Markov Models
Signal Processing
A hybrid method for three segmentation level of handwritten Arabic script
Proceedings of the International Workshop on Multilingual OCR
HMM-based system for recognizing words in historical Arabic manuscript
International Journal of Robotics and Automation
Human reading based strategies for off-line Arabic word recognition
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Mono-font cursive arabic text recognition using speech recognition system
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Offline handwritten arabic character segmentation with probabilistic model
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Automated system for Arabic optical character recognition
Proceedings of the 3rd International Conference on Information and Communication Systems
Offline arabic handwritten text recognition: A Survey
ACM Computing Surveys (CSUR)
Segmentation of Arabic Characters: A Comprehensive Survey
International Journal of Technology Diffusion
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Character segmentation is a necessary preprocessing step for character recognition in many OCR systems. It is an important step because incorrectly segmented characters are unlikelyto be recognized correctly. The most difficult case in character segmentation is the cursivescript. The scripted nature of Arabic written language poses some high challenges for automatic character segmentat on and recognition. In this paper a new character segmentation algorithm (ACSA) of Arabic scripts is presented. The developed segmentation algorithm yields on the segmentation of isolated handwritten words in perfectly separated characters. It is based on morphological rules which are constructed at the feature extraction phase. Finally ACSA is combined with an existing handwritten Arabic character recognition system (RECAM).