• DocumentCode
    2772889
  • Title

    On-line handwritten formula recognition using statistical methods

  • Author

    Kosmala, Andreas ; Rigoll, Gerhard

  • Author_Institution
    Fac. of Electr. Eng., Gerhard-Mercator-Univ., Duisburg, Germany
  • Volume
    2
  • fYear
    1998
  • fDate
    16-20 Aug 1998
  • Firstpage
    1306
  • Abstract
    This paper presents the design of a system for the processing and recognition of online handwritten mathematical formulas. The hidden Markov model (HMM) based system is trained and evaluated with a writer dependent database consisting of 100 formulas for the training and an additional set of 30 formulas for the test. With the introduction of some constraints, it is possible to obtain high recognition rates up to 97.7%, and to transform the transcriptions of the formulas into TE X-syntax in order to achieve a convenient visualization of the results
  • Keywords
    character sets; handwritten character recognition; statistical analysis; HMM-based system; TEX-syntax; hidden Markov model; online handwritten mathematical formulas; statistical methods; writer dependent database; Communication channels; Computer science; Handwriting recognition; Hidden Markov models; Humans; Man machine systems; Speech recognition; Statistical analysis; System testing; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
  • Conference_Location
    Brisbane, Qld.
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-8512-3
  • Type

    conf

  • DOI
    10.1109/ICPR.1998.711941
  • Filename
    711941
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2772889