• DocumentCode
    3207233
  • Title

    Voronoi skeletons: theory and applications

  • Author

    Ogniewicz, R. ; Ilg, M.

  • Author_Institution
    ETH Zurich, Switzerland
  • fYear
    1992
  • fDate
    15-18 Jun 1992
  • Firstpage
    63
  • Lastpage
    69
  • Abstract
    A novel method of robust skeletonization based on the Voronoi diagram of boundary points, which is characterized by correct Euclidean metries and inherent preservation of connectivity, is presented. The regularization of the Voronoi medial axis (VMA) in the sense of H. Blum´s (1967) prairie fire analogy is done by attributing to each component of the VMA a measure of prominence and stability. The resulting Voronoi skeletons appear largely invariant with respect to typical noise conditions in the image and geometric transformations. Hierarchical clustering of the skeleton branches, the so-called skeleton pyramid, leads to further simplification of the skeleton. Several applications demonstrate the suitability of the Voronoi skeleton to higher-order tasks such as object recognition
  • Keywords
    computational geometry; computer vision; image processing; image recognition; Euclidean metries; Voronoi diagram; Voronoi medial axis; Voronoi skeletons; boundary points; geometric transformations; noise conditions; object recognition; prairie fire analogy; prominence; robust skeletonization; skeleton branches; skeleton pyramid; stability; Euclidean distance; Fires; Laboratories; Object recognition; Robustness; Shape; Skeleton; Stability; Testing; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
  • Conference_Location
    Champaign, IL
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2855-3
  • Type

    conf

  • DOI
    10.1109/CVPR.1992.223226
  • Filename
    223226