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A Printed Chinese Character Recognition Method Based on Area Brightness Feature

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Chinese Lexical Semantics (CLSW 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11831))

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Abstract

This paper proposes a method for printed Chinese character recognition based on the area brightness feature, which is simple and has a low computational cost. It can achieve over 93% accuracy in recognizing printed Chinese characters equal to or greater than 10.5 pt which can meet the needs of certain situations (such as screen capture). The disadvantage of this method is its poor anti-distortion handling ability, and the recognition accuracy of smaller images still needs to be improved.

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References

  1. Stallings, W.: Approaches to Chinese character recognition. Pattern Recogn. 8(2), 87–98 (2004)

    Article  Google Scholar 

  2. Mori, S., Yamamoto, K., Yasuda, M.: Research on machine recognition of handprinted characters. IEEE Trans. Pattern Anal. Mach. Intell. 6(4), 386–405 (1984)

    Article  Google Scholar 

  3. Liu, C.-L., Jaeger, S., Nakagawa, M.: Online recognition of Chinese characters: the state-of-the-art. IEEE Trans. Pattern Anal. Mach. Intell. 26(2), 198–213 (2004)

    Article  Google Scholar 

  4. Liu, J.: Study and realization on printed Chinese character recognition system. Dalian University of Technology, Dalian (2011)

    Google Scholar 

  5. An, R., Zhang, S., Chen, H.: Method for removing burr to optical character recognition. Comput. Technol. Dev. 17(9), 136–138 (2007)

    Google Scholar 

  6. Liu, B., Xiao, H.: Printed Chinese character recognition based on non-separable wavelet transform and Zernike moments. Comput. Appl. Softw. 35(4), 229–236 (2018)

    Google Scholar 

  7. Zhang, J., Zhu, Y., Du, J., Dai, L.: Radical Analysis Network for Zero-shot Learning in Printed Chinese Character Recognition. arXiv:1711.01889 (2018)

  8. State Council of the PRC: General Standard Chinese Character List. http://www.gov.cn/zwgk/2013-08/19/content_2469793.htm

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Acknowledgments

This research is sponsored by the Major Project of National Social Science Foundation of China (15ZDB096) and Major Projects of the Key Research Base of Humanities and Social Sciences of the Ministry of Education (19JJD740003).

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Authors and Affiliations

  1. Research Center for Folklore, Classics and Chinese Characters, Beijing Normal University, Beijing, China

    Yonghong Ke

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  1. Yonghong Ke
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Correspondence to Yonghong Ke .

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Editors and Affiliations

  1. National Taiwan Normal University, Taipei, Taiwan

    Jia-Fei Hong

  2. Beijing Information Science and Technology University, Beijing, China

    Yangsen Zhang

  3. Beijing Language and Culture University, Beijing, China

    Pengyuan Liu

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Ke, Y. (2020). A Printed Chinese Character Recognition Method Based on Area Brightness Feature. In: Hong, JF., Zhang, Y., Liu, P. (eds) Chinese Lexical Semantics. CLSW 2019. Lecture Notes in Computer Science(), vol 11831. Springer, Cham. https://doi.org/10.1007/978-3-030-38189-9_35

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  • DOI: https://doi.org/10.1007/978-3-030-38189-9_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38188-2

  • Online ISBN: 978-3-030-38189-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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