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Multifont Arabic Characters Recognition Using HoughTransform and Neural Networks

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

Pattern recognition is a well-established field of study and Optical Character Recognition (OCR) has long been seen as one of its important contributions. However, Arabic has been one of the last major languages to receive attention. This paper describes the performance of an approach combining Hough transform in features extraction and Neural Networks in classification. Experimental tests have been carried out on a set of 85.000 samples of characters corresponding to5 different fonts. Some promising experimental results are reported.

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References

  • Amin, A.: Arabic Character Recognition. Handbook of Character Recognition and Document Image Analysis, pp. 397–420. World Scientific Publishing Company, Singapore (1997)

    Google Scholar 

  • Amor, N.B., Amara, N.: Applying Neural Networks and Wavelet Transform to Multifont Arabic Character Recognition. International Conference on Computing. In: Communications and Control Technologies (CCCT 2004), Austin (Texas), USA, August 14-17 (2004)

    Google Scholar 

  • Klassen, T.: Towards Neural Network Recognition Of Handwritten Arabic Letters. Dalhousie University (2001)

    Google Scholar 

  • Lippmann, R.: Pattern Classification using Neural Networks. IEEE Communications Magazine (1989)

    Google Scholar 

  • Brown, E.W.: Character Recognition by Feature Point Extraction. Northeastern University internal paper (1992)

    Google Scholar 

  • Amor, N.B., Amara, N.: Hidden Markov Models and Wavelet Transform in Multifont Arabic Characters Recognition. In: International Conference on Computing, Communications and Control Technologies (CCCT 2005), Austin, Texas, USA, Silicon Hills, July 24-27 (2005)

    Google Scholar 

  • Illingworth, J., Kittler, J.: A Survey of the Hough Transform. Computer Vision, Graphics and Image Processing 44, 87–116 (1988)

    Article  Google Scholar 

  • Altuwaijri, M.M., Bayoumi, M.A.: Arabic Text Recognition Using Neural Network. In: ISCAS 1994 IEEE International Symposium on Circuits and systems, vol. 6 (1994)

    Google Scholar 

  • Amor, N.B., Amara, N.: Multifont Arabic Character Recognition Using Hough Transform and Hidden Markov Models. In: ISPA 2005 IEEE 4th International Symposium on Image and Signal Processing and Analysis, Zagreb, Croatia, September 15-17 (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Laboratory of Systems and Signal Processing (LSTS), National Engineering School of Tunis (ENIT), Tunisia

    Nadia Ben Amor

  2. Laboratory of Systems and Signal Processing (LSTS), National Engineering School of Sousse (ENISo), Tunisia

    Najoua Essoukri Ben Amara

Authors
  1. Nadia Ben Amor
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  2. Najoua Essoukri Ben Amara
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Ben Amor, N., Essoukri Ben Amara, N. (2006). Multifont Arabic Characters Recognition Using HoughTransform and Neural Networks. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_43

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  • DOI: https://doi.org/10.1007/11760023_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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