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International Conference Image Analysis and Recognition

ICIAR 2013: Image Analysis and Recognition pp 711–716Cite as

Chinese Character Recognition by Krawtchouk Moment Features

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7950))

Abstract

Moment descriptors have long been applied in object recognition since the early years of the development of the moment theories. Nowadays, discrete orthogonal moments have been studied and proposed for they are superior to traditional continuous ones. In this paper, a set of moment features extracted from the discrete Krawtchouk moments for Chinese character recognition is presented. A new method of evaluating the variance values of each moment feature is applied in this research. Tested on a set of 6,763 Chinese characters, our newly proposed Krawtchouk moment features perform very well in distinguishing all Chinese character pairs that have similar structures.…

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Author information

Authors and Affiliations

  1. University of Winnipeg, Winnipeg, Manitoba, Canada

    Bing Hu & Simon Liao

Authors
  1. Bing Hu
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  2. Simon Liao
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2013 Springer-Verlag Berlin Heidelberg

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Cite this paper

Hu, B., Liao, S. (2013). Chinese Character Recognition by Krawtchouk Moment Features. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_81

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  • DOI: https://doi.org/10.1007/978-3-642-39094-4_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39093-7

  • Online ISBN: 978-3-642-39094-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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