• DocumentCode
    3019136
  • Title

    An HMM implementation for on-line handwriting recognition based on pen-coordinate feature and pen-direction feature

  • Author

    Okumura, Daiki ; Uchida, Seiichi ; Sakoe, Hiroaki

  • Author_Institution
    Graduate Sch. of Inf. Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan
  • fYear
    2005
  • fDate
    29 Aug.-1 Sept. 2005
  • Firstpage
    26
  • Abstract
    An on-line handwritten character recognition technique based on a new HMM is proposed. In the proposed HMM, not only pen-direction feature but also pen-coordinate feature are separately utilized for describing the shape variation of on-line characters accurately. Specifically speaking, the proposed HMM outputs a pen-coordinate feature at each inter-state transition and outputs a pen-direction feature at each intra-state transition, i.e., self-transition. Thus, each state of the proposed HMM can specify the starting position and the direction of a line segment by its incoming inter-state transition and intra-state transition, respectively. The results of recognition experiments on 10-stroke Chinese characters show that the proposed HMM outperforms the conventional HMM which does not use the pen-coordinate feature because of its non-stationarity.
  • Keywords
    feature extraction; handwritten character recognition; hidden Markov models; 10-stroke Chinese characters; hidden Markov models; inter-state transition; intra-state transition; on-line handwriting recognition; pen-coordinate feature; pen-direction feature; Character recognition; Deformable models; Handwriting recognition; Hidden Markov models; Information science; Proposals; Shape; Solid modeling; Tellurium; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
  • ISSN
    1520-5263
  • Print_ISBN
    0-7695-2420-6
  • Type

    conf

  • DOI
    10.1109/ICDAR.2005.50
  • Filename
    1575504