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Robust Chinese Character Recognition by Selection of Binary-Based and Grayscale-Based Classifier

  • Yoshinobu Hotta
  • Jun Sun
  • Yutaka Katsuyama
  • Satoshi Naoi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3872)

Abstract

As the spread of digital videos, digital cameras, and camera phones, lots of researches are reported about degraded character recognition. It is found that while the grayscale-based classifier is powerful for degraded character, the performance for clear character is not so good as binary-based classifier. In this paper, a dynamic classifier selection method is proposed to combine the two classifiers based on an estimation of the degradation level and the recognition reliability of the input character images. Experimental results show that the proposed method can achieve better recognition performance than the two individual ones.

Keywords

Recognition Rate Recognition Accuracy Character Recognition Camera Phone Degradation Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yoshinobu Hotta
    • 1
  • Jun Sun
    • 2
  • Yutaka Katsuyama
    • 1
  • Satoshi Naoi
    • 1
  1. 1.FUJITSU LABORATORIES LTD.KawasakiJapan
  2. 2.FUJITSU R&D CENTER Co.,Ltd.BeijingP.R. China

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