• DocumentCode
    1304088
  • Title

    Angular bisector network, a simplified generalized Voronoi diagram: application to processing complex intersections in biomedical images

  • Author

    Cloppet, Florence ; Oliva, Jean-Michel ; Stamon, George

  • Author_Institution
    Lab. SIP-CRIPS, Univ. Rene Descartes, Paris, France
  • Volume
    22
  • Issue
    1
  • fYear
    2000
  • fDate
    1/1/2000 12:00:00 AM
  • Firstpage
    120
  • Lastpage
    128
  • Abstract
    One of the major goals of computer vision is the research and the development of flexible methods for shape description. A large group of shape description techniques is given by heuristic approaches, which yield acceptable results in the description of simple shapes and regions. In this case, objects are represented by a planar graph with nodes symbolizing subregions from region decomposition, and region shape is then described by the graph properties. In the paper, the angular bisector network (ABN), a descriptor of polygonal shape, is used to automatically detect intersections between neurites of cell structures. Some properties of the ABN, such as linear algebraic complexity, easy extraction of characteristic points, etc., are very useful and experimental results are promising
  • Keywords
    computational complexity; computational geometry; computer vision; graph theory; medical image processing; angular bisector network; biomedical images; complex intersections; flexible methods; graph properties; heuristic approaches; linear algebraic complexity; polygonal shape; shape description; simplified generalized Voronoi diagram; Application software; Atherosclerosis; Biomedical computing; Biomedical imaging; Costs; Graph theory; Robots; Senior members; Shape; Skeleton;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.824824
  • Filename
    824824