• DocumentCode
    293578
  • Title

    Multiresolution skeletonization an electrostatic field-based approach

  • Author

    Abdel-Hamid, Gamal H. ; Yang, Yee-Hong

  • Author_Institution
    Dept. of Comput. Sci., Saskatchewan Univ., Saskatoon, Sask., Canada
  • Volume
    1
  • fYear
    1994
  • fDate
    13-16 Nov 1994
  • Firstpage
    949
  • Abstract
    Skeleton representation of an object is believed to be a powerful representation that captures both boundary and region information of the object. The skeleton of a shape is a representation composed of idealized thin lines that preserve the connectivity or topology of the original shape. Although the literature contains a large number of skeletonization algorithms, many open problems remain. A new skeletonization approach that relies on the electrostatic field theory (EFT) is proposed. Many problems associated with existing skeletonization algorithms are solved using the proposed approach. In particular, connectivity, thinness, and other desirable features of a skeleton are guaranteed. Furthermore, the electrostatic field-based approach captures notions of corner detection, multiple scale, thinning, and skeletonization all within one unified framework. Experimental results are very encouraging and are used to illustrate the potential of the proposed approach
  • Keywords
    edge detection; electrostatics; feature extraction; image representation; image resolution; boundary information; corner detection; electrostatic field theory; electrostatic field-based approach; experimental results; idealized thin lines; multiple scale; multiresolution skeletonization; object representation; region information; shape connectivity; shape skeleton; shape topology; skeleton representation; skeletonization algorithms; thinness; thinning; Computer vision; Councils; Detectors; Electrostatics; Laboratories; Postal services; Shape; Skeleton; Sun; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
  • Conference_Location
    Austin, TX
  • Print_ISBN
    0-8186-6952-7
  • Type

    conf

  • DOI
    10.1109/ICIP.1994.413249
  • Filename
    413249