• DocumentCode
    1982773
  • Title

    Study of off-line handwritten Chinese character recognition based on dynamic pruned FSVMs

  • Author

    Zhu, Cheng-hui ; Shi, Chang-yu ; Wang, Jian-ping ; Xu, Xiao-bing

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Hefei Univ. of Technol., Hefei, China
  • fYear
    2011
  • fDate
    16-18 Sept. 2011
  • Firstpage
    395
  • Lastpage
    398
  • Abstract
    According to the off-line handwritten Chinese characters, a classification and recognition method which is combined by pruning FSVM coarse classification and SVM fine classification is proposed in this text .First cut no value minor to reduce the number of support vector machines, and then determine the coarse classification through fuzzy membership when the coarse classification is done. In fine classification, OAA SVM algorithm is used to achieve the same Chinese characters recognition. The simulation result shows that this method can improve the recognition rate and speed of off-line handwritten Chinese.
  • Keywords
    fuzzy set theory; handwriting recognition; image classification; natural language processing; support vector machines; FSVM coarse classification; dynamic pruned FSVM; fuzzy membership; handwritten Chinese character recognition; support vector machines; Character recognition; Classification algorithms; Complexity theory; Feature extraction; Heuristic algorithms; Support vector machines; Training; FSVM; membership; multi-classification; offline handwritten Chinese characters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2011 International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4244-8162-0
  • Type

    conf

  • DOI
    10.1109/ICECENG.2011.6057497
  • Filename
    6057497