• DocumentCode
    2028973
  • Title

    On-line handwritten documents segmentation

  • Author

    Blanchard, J. ; Artieres, Thierry

  • Author_Institution
    LIP6, Paris VI Univ., France
  • fYear
    2004
  • fDate
    26-29 Oct. 2004
  • Firstpage
    148
  • Lastpage
    153
  • Abstract
    This work concerns note-taking applications. It deals with poorly structured on-line handwritten documents segmentation such as pages of handwritten notes. We extend an existing system based on probabilistic feature grammars. The probabilistic nature of this system allows considering lots of segmentation hypothesis, which is an advantage for poorly structured documents processing, but it goes with important algorithmic complexity. Our improvements concern the handling of this complexity using genetic algorithms, the definition of performance measurements that are adapted to the segmentation of on-line documents, and the evaluation of this segmentation approach on a collection of documents of various qualities.
  • Keywords
    document image processing; genetic algorithms; grammars; handwritten character recognition; image segmentation; genetic algorithm; handwritten notes; online handwritten documents segmentation; probabilistic feature grammar; Conferences; Design methodology; Document handling; Genetic algorithms; Handwriting recognition; Histograms; Ink; Measurement; Production; Text analysis; Genetic algorithms; Poorly structured documents; Probabilistic grammars; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on
  • ISSN
    1550-5235
  • Print_ISBN
    0-7695-2187-8
  • Type

    conf

  • DOI
    10.1109/IWFHR.2004.78
  • Filename
    1363902