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Off-line handwritten Chinese character recognition based on fusion features and Bayesian classifier

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Soft Computing as Transdisciplinary Science and Technology

Part of the book series: Advances in Soft Computing ((AINSC,volume 29))

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Abstract

Off-line handwritten Chinese character recognition (Off-HCCR) is one of the most challenging topics in pattern recognition. This paper first presents to use Gabor filters and Zernike moments to extract local and global features of handwritten Chinese characters. Then, fusion features are classified by naïve Bayesian network, which performs surprisingly well when inputted features are conditionally independent. A recognition system based on these approaches is built, and experiments are performed on 50 categories frequently used handwritten Chinese characters. Results indicate that the proposed methods are effective.

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References

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Author information

Authors and Affiliations

  1. Satellite Venture Business Laboratory, Muroran Institute of Technology, Muroran, 050-8585, Japan

    Yanyu Gao

  2. Department of Computer Science and Systems Engineering, Muroran Institute of Technology, Muroran, 050-8585, Japan

    Takashi Uozumi

  3. Haidian District, JF Computer System Co., Ltd, Beijing, 100083, China

    Fei Chen

Authors
  1. Yanyu Gao
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  2. Takashi Uozumi
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  3. Fei Chen
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, Oklahoma State University, North Greenwood Avenue 700, 74106, Tulsa, USA

    Ajith Abraham

  2. Dept. of Computer Science and Systems Engineering, Muroran Institute of Technology, Mizumoto-cho 27-1, 050-8585, Muroran, Hokkaido, Japan

    Yasuhiko Dote

  3. Dept. of Computational Science and Engineering, Nagoya University, Furo-cho, Chikusa-ku, 464-8601, Nagoya, Aichi-ken, Japan

    Takeshi Furuhashi

  4. Institut für Sicherheits-/Prüftechnik, Fraunhofer IPK Berlin, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  5. Division of Complex Systems Technology Graduate School of Engineering, University of Hokkaido, N-13, W-8 060 KITA-KU, Sapporo, Japan

    Azuma Ohuchi

  6. PRESTO Japan Science & Technology Corp. GSSM, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, 12-0012, Tokyo, Japan

    Yukio Ohsawa

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© 2005 Springer-Verlag Berlin Heidelberg

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Gao, Y., Uozumi, T., Chen, F. (2005). Off-line handwritten Chinese character recognition based on fusion features and Bayesian classifier. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_62

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  • DOI: https://doi.org/10.1007/3-540-32391-0_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25055-5

  • Online ISBN: 978-3-540-32391-4

  • eBook Packages: EngineeringEngineering (R0)

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