A Markovian Engine for Text Recognition: - Cursive Arabic Text, Statistical Features and Interconnected HMMs
نویسندگان
چکیده
This paper presents a cursive Arabic text recognition system. The system decomposes the document image into text line images and extracts a set of simple statistical features from a one-pixel width window which is sliding a cross that text line. It then injects the resulting feature vectors to Hidden Markov Models. The proposed system is applied to a data corpus which includes Arabic text of more than 600 A4-size sheets typewritten in multiple computer-generated fonts.
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