A markovian engine for text recognition: cursive arabic text, statistical features and interconnected HMMs

Authors:
M. S. Khorsheed;H. Al-Omari
Affiliations:
Image Processing and Signal Analysis & Recognition (IPSAR) Research Group, Computer Research Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia;Image Processing and Signal Analysis & Recognition (IPSAR) Research Group, Computer Research Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
Venue:
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Year:
2012

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Abstract

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.