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Printed Arabic character recognition using HMM

  • Pattern Recognition and Image Processing
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Abstract

The Arabic Language has a very rich vocabulary. More than 200 million people speak this language as their native speaking, and over 1 billion people use it in several religion-related activities. In this paper a new technique is presented for recognizing printed Arabic characters. After a word is segmented, each character/word is entirely transformed into a feature vector. The features of printed Arabic characters include strokes and bays in various directions, endpoints, intersection points, loops, dots and zigzags. The word skeleton is decomposed into a number of links in orthographic order, and then it is transferred into a sequence of symbols using vector quantization. Single hidden Markov model has been used for recognizing the printed Arabic characters. Experimental results show that the high recognition rate depends on the number of states in each sample.

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Authors and Affiliations

  1. Computer Science Department, Harbin Institute of Technology, 150001, Harbin, P.R. China

    Abbas H. Hassin, Xiang-Long Tang, Jia-Feng Liu & Wei Zhao

Authors
  1. Abbas H. Hassin
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  2. Xiang-Long Tang
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  3. Jia-Feng Liu
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  4. Wei Zhao
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Corresponding author

Correspondence to Abbas H. Hassin.

Additional information

Abbas H. Hassin received the B.Sc. and M.Sc. degrees in computer science from Basrah University, Iraq in 1990 and 1995, respectively. From 1992–1995 he was a director of Database Information and Electronic Survey Division at College of Engineering in Basrah University. From 1995–2001 he was a lecturer at College of Science at the same university. Currently, he is a Ph.D. candidate in computer science at Harbin Institute of Technology (HIT), China. His research interests are Pattern Recognition and Character Recognition.

Xiang-Long Tang is the director of the T&R Division of pattern recognition and intelligent system at Harbin Institute of Technology, deputy director of Wearable Computer Engineering Center. He is a member of Council of Pattern Recognition and Machine Intelligence, Chinese Automation Society. His research field includes character recognition, image recognition, Chinese information processing, palm computer, biometrics computing. Prof. Tang has led 8 projects sponsored by the state, ministry/province and international cooperation. He has won a third prize of National Science and Technology Progress, a second prize, a third prize of Ministry level for Science and Technology Progress.

Jia-Feng Liu is an associate professor of Harbin Institute of Technology. He received B.S. and Ph.D. degrees from Harbin Institute of Technology (HIT) in 1990 and 1996 respectively. His research interests include pattern recogntiion, image processing and artificial intelligence.

Wei Zhao received her M.S. degree in pattern recognition and intelligence system from HIT in 2000. She worked on signature verification and word recognition in HIT from 1998. She is now a lecturer and a Ph.D. candidate at School of Computer Science and Technology, HIT. Her current research interests include pattern recognition, continuous character recognition and Chinese information process.

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Hassin, A.H., Tang, XL., Liu, JF. et al. Printed Arabic character recognition using HMM. J. Compt. Sci. & Technol. 19, 538–543 (2004). https://doi.org/10.1007/BF02944755

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  • DOI: https://doi.org/10.1007/BF02944755

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