• DocumentCode
    2022567
  • Title

    Document Image Segmentation Using a 2D Conditional Random Field Model

  • Author

    Nicolas, Stéphane ; Dardenne, Julien ; Paquet, Thierry ; Heutte, Laurent

  • Author_Institution
    Univ. de Rouen, Mont Saint Aignan
  • Volume
    1
  • fYear
    2007
  • fDate
    23-26 Sept. 2007
  • Firstpage
    407
  • Lastpage
    411
  • Abstract
    This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into account and to integrate contextual knowledge, while taking benefit from machine learning techniques. Experiments on handwritten drafts of Flaubert show that these models provide interesting solutions.
  • Keywords
    document image processing; image segmentation; learning (artificial intelligence); random processes; 2D conditional random field model; document image segmentation; machine learning; Context modeling; Handwriting recognition; Image analysis; Image recognition; Image segmentation; Image sequence analysis; Labeling; Probability; Stochastic processes; Text analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
  • Conference_Location
    Parana
  • ISSN
    1520-5363
  • Print_ISBN
    978-0-7695-2822-9
  • Type

    conf

  • DOI
    10.1109/ICDAR.2007.4378741
  • Filename
    4378741
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2022567