• DocumentCode
    1580609
  • Title

    New paradigm for segmentation and recognition of handwritten numeral string

  • Author

    Yoon, Sungsoo ; Kim, Gyeonghwan ; Choi, Yeongwoo ; Lee, Yillbyung

  • Author_Institution
    Dept. of Comput. Sci., Yonsei Univ., Seoul, South Korea
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    205
  • Lastpage
    209
  • Abstract
    String recognition is rather paradoxical problem because it requires the segmentation of the string into understandable units, but proper segmentation needs a-priori knowledge of the units and this implies a recognition capability. To solve this dilemma therefore, both a-priori knowledge of meaningful units and a segmentation method have to be used together, and they should dynamically interact with each other. In other words, the results of segmentation are used as fundamental information to suppose what is most likely to be, and then its a-priori knowledge is used to help the segmentation. This model makes explicit segmentation unnecessary because it does not speculate on possible break positions. It is also possible to recognize a digit even if it contains strokes that do not belong to to it. Using this paradigm for 100 handwritten numeral strings belonging to the NIST database has resulted in 95% recognition
  • Keywords
    handwritten character recognition; image segmentation; optical character recognition; NIST database; a-priori knowledge; break positions; digit recognition; dynamically interacting methods; handwritten numeral string recognition; string segmentation; understandable units; Character recognition; Computational complexity; Computer science; Databases; Handwriting recognition; Hidden Markov models; Image segmentation; Knowledge engineering; NIST; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7695-1263-1
  • Type

    conf

  • DOI
    10.1109/ICDAR.2001.953784
  • Filename
    953784