• DocumentCode
    3488842
  • Title

    A Stroke Order Verification Method for On-Line Handwritten Chinese Characters Based on Tempo-spatial Consistency Analysis

  • Author

    Rongsha Li ; Liangrui Peng ; Endong Xun ; Nan Wei

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • fYear
    2013
  • fDate
    25-28 Aug. 2013
  • Firstpage
    999
  • Lastpage
    1003
  • Abstract
    This paper proposes a method to recognize stroke orders of on-line handwritten Chinese characters based on analyzing both spatial and temporal information. A novel control-point-based analysis method is presented for spatial information analysis to match strokes with various shapes and styles. Its computation complexity is much lower than image correlation method and is suitable for applications on mobile devices. For temporal information analysis, Hidden Markov Model is adopted and a proposed rectification method is integrated to find the optimal pair-wise matching result of stroke sequences. Experimental results proved the effectiveness of the proposed method. The verification rate is 99.6% on the test set.
  • Keywords
    computational complexity; handwritten character recognition; hidden Markov models; image matching; image sequences; natural language processing; spatiotemporal phenomena; computational complexity; control-point-based analysis method; hidden Markov model; image correlation method; mobile devices; on-line handwritten Chinese characters; optimal pair-wise matching; rectification method; spatial information analysis; stroke matching; stroke order verification method; stroke sequences; tempo-spatial consistency analysis; temporal information analysis; Algorithm design and analysis; Character recognition; Correlation; Hidden Markov models; Shape; Vectors; Viterbi algorithm; on-line handwritten Chinese character; stroke order verification; tempo-spatial consistency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2013.201
  • Filename
    6628766