• DocumentCode
    3308478
  • Title

    Hybrid thinning through reconstruction

  • Author

    Doermann, David ; Kia, Omid

  • Author_Institution
    Center for Autom. Res., Maryland Univ., College Park, MD, USA
  • Volume
    2
  • fYear
    1995
  • fDate
    14-16 Aug 1995
  • Firstpage
    632
  • Abstract
    One difficulty with many pixel-wise thinning algorithms is that they produce unacceptable results at junction points, or in the presence of contour noise. The authors present a novel approach to detecting ambiguous regions in a thinned image. The method uses the reconstructability properties of appropriate thinning algorithms to reverse the thinning process and automatically detect those pixels which may have resulted from more then one stroke in the image. The ambiguous regions are then interpreted and reconstructed using domain specific or derived contextual information. The approach has the advantage of using local methods to rapidly identify strokes (or regions) which have been thinned correctly and allowing more detailed analysis based on non-local methods in the remaining regions
  • Keywords
    edge detection; image reconstruction; image segmentation; noise; ambiguous region detection; automatic pixel detection; contextual information; contour noise; hybrid thinning; image reconstruction; image stroke; junction points; local methods; nonlocal methods; pixel-wise thinning algorithms; Algorithm design and analysis; Automation; Educational institutions; Image reconstruction; Pattern analysis; Pattern recognition; Pixel; Shape; Skeleton; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    0-8186-7128-9
  • Type

    conf

  • DOI
    10.1109/ICDAR.1995.601975
  • Filename
    601975