• DocumentCode
    3320229
  • Title

    On-line cursive script recognition using an island-driven search technique

  • Author

    Lee, Seung-Ho ; Lee, HyunKyu ; Kim, Jin H.

  • Author_Institution
    Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
  • Volume
    2
  • fYear
    1995
  • fDate
    14-16 Aug 1995
  • Firstpage
    886
  • Abstract
    A new approach for on-line cursive script recognition that combines a letter spotting technique with an island-driven lattice search algorithm is presented. Initially, all plausible letter components within an input pattern are detected, using a letter spotting technique based on hidden Markov models. A word hypothesis lattice is generated as a result of the letter spotting. Then an island-driven search algorithm is performed to find the optimal path on the word hypothesis lattice, which corresponds to the most probable word among the dictionary words. The results of this experiment suggest that the proposed method works effectively in recognizing English cursive words. In a word recognition test, the average 85.4% word accuracy was obtained
  • Keywords
    handwriting recognition; hidden Markov models; optical character recognition; search problems; English cursive words; hidden Markov models; island-driven search technique; letter spotting technique; on-line cursive script recognition; word hypothesis lattice; word recognition test; Computer science; Data structures; Electronic mail; Handwriting recognition; Hidden Markov models; Image recognition; Lattices; Shape; Speech recognition; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    0-8186-7128-9
  • Type

    conf

  • DOI
    10.1109/ICDAR.1995.602043
  • Filename
    602043