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A New Method for Character Segmentation and Skew Correction on Chinese Seal Images

  • Chao Ren
  • Youbin Chen
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 128)

Abstract

In this paper, a new method for automatic character segmentation and skew correction on Chinese seal images is proposed. Traditional methods [1] using shapes of Chinese characters on circular seals sometimes lead to inaccurate transformation of the Chinese characters and thus lose a lot of detailed information. It is hard for these methods to apply Chinese character recognition technology with automatic seal image retrieval. In addition, traditional methods [1] which were designed for circular seal images cannot work well for elliptical seal images. In order to overcome these shortcomings, we propose a new method to segment the Chinese characters on both circular and elliptical seal images. Our method first fits the contour of seal images and then classifies them into either circular seal shape or elliptical seal shape. After that, we apply different methods for Chinese character segmentation and skew correction with circular and elliptical seal shape images respectively. Experimental results show that our method has better performance than traditional methods.

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References

  1. 1.
    Liu, H., Lu, Y., Wu, Q., Zha, H.: Automatic Seal Image Retrieval Method by Using Shape Features of Chinese Characters. In: ICSMC, pp.2871–2876 (2007)Google Scholar
  2. 2.
    Ueda, K., Matsuo, K.: Automatic Seal Imprint Verification System for Bank check Processing. In: ICITA, vol. 1, pp. 768–771 (2005)Google Scholar
  3. 3.
    Ueda, K., Mutoh, T., Matsuo, K.: Automatic verification system for seal imprints on Japanese bank checks. In: ICPR, vol. 1, pp. 629–632 (1998)Google Scholar
  4. 4.
    Halif, R., Flusser, J.: Numerically Stable Direct Least Squares Fitting of Ellipses. Department of Software Engineering, Charles University, Czech Republic (2000)Google Scholar
  5. 5.
    Matsuura, T., Mori, K.: Rotation Invariant Seal Imprint Verification Method. In: Yamazakiv, K. (ed.) ICECS, vol. 3, pp. 955–958 (2002)Google Scholar
  6. 6.
    Matsuura, T., Ymazakiv, K.: Seal imprint verification with rotation invariance. Circuits and Systems, 597–600 (2004)Google Scholar
  7. 7.
    Wang, X., Chen, Y.: Seal Image Registration Based on Shape and Layout Characteristics. In: CISP, vol. 7, pp. 3440–3444 (2009)Google Scholar
  8. 8.
    Roy, P.P., Pal, U., Llados, J.: Seal Detection and Recognition: An Approach for Document Indexing. In: ICDAR, pp. 101–105 (2009)Google Scholar
  9. 9.
    Wang, N.: Seal Identification Based on Pixel Distribution Probability with Three-Mode and Nine-Section. In: CSSE, vol. 3, pp. 742–745 (2008)Google Scholar
  10. 10.
    Cheng, Y.: Seal Recognition using the Shape Selection Algorithm. In: EIT, pp. 544–547 (2006)Google Scholar
  11. 11.
    Ueda, K.: Extraction of signature and seal imprint from bank checks by using color information. In: ICDAR, vol. 2, pp. 665–668 (1995)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Graduate School at ShenzhenTsinghua UniversityShenzhenChina

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