• DocumentCode
    1889605
  • Title

    Geometrical Algorithms to Detect Patterns from a Set of Points

  • Author

    Bougleux, Sébastien ; Melkemi, Mahmoud ; Elmoataz, Abderrahim

  • Author_Institution
    GREYC CNRS, Caen
  • fYear
    2006
  • fDate
    2-5 July 2006
  • Firstpage
    94
  • Lastpage
    101
  • Abstract
    This article presents a new approach for detecting patterns, such as lines, parabolas and circles, from a two- dimensional cloud of points S. This scheme transforms the problem of detecting the patterns from S, to the problem of detecting simpler patterns from a set of points S1 computed from the Voronoi and Delaunay diagrams of S. It is based on the differential properties of the Voronoi diagram that reflect the patterns to be retrieved. For example, in the case of parabolas, the patterns to be detected in S´ are straight lines. The general idea of using the Voronoi diagram to detect patterns is an alternative and a complementary approach to the Hough Transform. It does not need to code a space of parameters and can be generalized to higher dimensions, with some adaptations.
  • Keywords
    Hough transforms; computational geometry; mesh generation; pattern recognition; Delaunay diagram; Hough transform; Voronoi diagram; geometrical algorithm; pattern detection; point cloud cluster group; point set; two-dimensional point cloud; Cloud computing; Computer vision; Equations; Face detection; Image reconstruction; Noise shaping; Pattern analysis; Robustness; Shape; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Voronoi Diagrams in Science and Engineering, 2006. ISVD '06. 3rd International Symposium on
  • Conference_Location
    Banff, Alberta, BC
  • Print_ISBN
    0-7695-2630-6
  • Type

    conf

  • DOI
    10.1109/ISVD.2006.23
  • Filename
    4124808