• DocumentCode
    3142654
  • Title

    The feature extraction of Chinese character based on contour information

  • Author

    Tao, Yu ; Tang, Yuan Y.

  • Author_Institution
    Dept. of Comput. Sci., Hong Kong Baptist Univ., Kowloon, Hong Kong
  • fYear
    1999
  • fDate
    20-22 Sep 1999
  • Firstpage
    637
  • Lastpage
    640
  • Abstract
    A new method, called central projection transformation, is proposed in this paper for feature extraction. From our experiments, the new method is found to be efficient in extracting features based on the contours of Chinese characters. Chinese characters have complex structures, and some of them are composed of several separate components, so several contours are embedded in a character. This may obstruct the application of the contour approach in recognizing Chinese characters. Central projection transformation can convert such a multi-contour pattern into a solid, convex pattern whose contour is a unique polygon. Most of the information of this new pattern is still located around its periphery. This approach can greatly simplify the processing of Chinese characters and other multi-contour patterns. It is also a powerful tool for processing Arabic, Japanese and other characters
  • Keywords
    edge detection; feature extraction; optical character recognition; Arabic characters; Chinese characters; Japanese characters; central projection transformation; character contour information; convex pattern; feature extraction; multi-contour patterns; polygon; Character recognition; Computer science; Electrical capacitance tomography; Feature extraction; Image analysis; Information analysis; Pattern classification; Pattern recognition; Performance analysis; Size measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    0-7695-0318-7
  • Type

    conf

  • DOI
    10.1109/ICDAR.1999.791868
  • Filename
    791868