• DocumentCode
    2396953
  • Title

    Handwritten Chinese character analysis and preclassification using stroke structural sequence

  • Author

    Chen, Zen ; Lee, Chi-Wei ; Cheng, Rei-Heng

  • Author_Institution
    Inst. of Comput. Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • Volume
    3
  • fYear
    1996
  • fDate
    25-29 Aug 1996
  • Firstpage
    89
  • Abstract
    A unique stroke ordering for handwritten Chinese characters is desirable in many applications including efficient character recognition and automatic radical extraction. Although there are some rules or conventions for writing Chinese characters, yet no consistent and complete rule set is available. Besides special radical knowledge is often needed. It is the purpose of this paper to propose a set of rules for stroke ordering for producing a unique stroke sequence for Chinese characters. It requires no special radical knowledge or knowledge of character block layouts, so it is easy for machine implementation. Moreover, the stroke sequences derived are similar to those given in the dictionary, if not the same. To deal with the writing, variations among writers, we generalize the derived stroke structure sequence to obtain a more consistent stroke information. This generalized stroke structural sequence can be used in the handwritten Chinese character preclassification. Experiments showing applications of our method are reported
  • Keywords
    character recognition; image classification; Chinese character preclassification; automatic radical extraction; character recognition; classification; handwritten Chinese character analysis; stroke ordering; stroke structural sequence; Application software; Character recognition; Computer science; Data mining; Databases; Dictionaries; Handwriting recognition; Humans; Shape; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1996., Proceedings of the 13th International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-7282-X
  • Type

    conf

  • DOI
    10.1109/ICPR.1996.546800
  • Filename
    546800