• DocumentCode
    2600039
  • Title

    Detecting Text Lines in Handwritten Documents

  • Author

    Li, Yi ; Zheng, Yefeng ; Doermann, David

  • Author_Institution
    Inst. for Adv. Comput. Studies, Maryland Univ., College Park, MD
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1030
  • Lastpage
    1033
  • Abstract
    Although detecting text lines in machine printed documents is typically considered a solved problem, it is still a challenge to segment handwritten text lines in the general sense given no prior knowledge of script. This paper models text line detection as an image segmentation problem by enhancing text line structures using a Gaussian window and adopting the level set method to evolve text line boundaries. Experiments show that the method, which is script independent, achieves high accuracy for detecting text lines in heterogeneous handwritten documents
  • Keywords
    document image processing; image enhancement; image segmentation; Gaussian window; handwritten documents; handwritten text line segmentation; image enhancement; image segmentation; machine printed documents; text line detection; Character recognition; Contracts; Educational institutions; Image analysis; Image segmentation; Laboratories; Level set; Merging; Noise level; Text analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.435
  • Filename
    1699383