• DocumentCode
    2622821
  • Title

    A printed Chinese character recognition method

  • Author

    Hu, Xiaobing ; Peng, Junjie ; Wang, MinChao ; Shen, Rong ; Huang, Kanrun ; Chen, Chang

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Shanghai Univ., Shanghai, China
  • fYear
    2011
  • fDate
    27-29 June 2011
  • Firstpage
    2904
  • Lastpage
    2907
  • Abstract
    Chinese character recognition is integrated technology that is related to pattern recognition, artificial intelligence, fuzzy mathematics, information theory, computer science and so on. Currently a lot of researches focused on the Chinese character recognition have been done, however, the results are still not very satisfactory. In this paper, A new recognition method is put forward based on the previous researches in this field and the combination of the statistical classification and neural networks. Using neural network to implement vector conversion and thus achieve the recognition of text, the method not only avoids the interference characteristics of Chinese structures, but also much improved the Chinese character recognition rate. Experiments with a large number of training samples show that the method of Chinese character recognition rate with the proposed method is more than 93%.
  • Keywords
    character recognition; image recognition; neural nets; statistical analysis; Chinese structures; artificial intelligence; computer science; fuzzy mathematics; information theory; interference characteristics; neural networks; pattern recognition; printed Chinese character recognition; statistical classification; text recognition; vector conversion; Artificial neural networks; Character recognition; Computer science; Image recognition; Publishing; Technological innovation; BP neural network; formatting; image binarization; insert (key words) Character recognition; style; styling; text refinement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Service System (CSSS), 2011 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-9762-1
  • Type

    conf

  • DOI
    10.1109/CSSS.2011.5974803
  • Filename
    5974803