• DocumentCode
    3019196
  • Title

    Estimating the pen trajectories of multi-path static scripts using hidden Markov models

  • Author

    Nel, E. ; du Preez, J.A. ; Herbst, B.M.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Stellenbosch Univ., South Africa
  • fYear
    2005
  • fDate
    29 Aug.-1 Sept. 2005
  • Firstpage
    41
  • Abstract
    Static handwritten scripts are available only as images on documents and by definition do not contain dynamic information. This study is about extracting dynamic information from a static handwritten script, specifically the sequence of pen positions that created the script. We assume that a dynamic representative of the static image is available (a different version typically obtained during an earlier registration process). A hidden Markov model (HMM) of the static image is compared with the dynamic representative to extract the dynamic information from the static image.
  • Keywords
    handwritten character recognition; hidden Markov models; image recognition; hidden Markov models; multipath static script; pen trajectories; static handwritten script; static image; Africa; Character recognition; Context modeling; Data mining; Handwriting recognition; Hidden Markov models; Mathematical model; Mathematics; Skeleton; Turning;
  • 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.2005.106
  • Filename
    1575507