• DocumentCode
    2609442
  • Title

    Finding convex edge groupings in an image

  • Author

    Huttenlocher, Daniel P. ; Wayner, Peter C.

  • Author_Institution
    Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA
  • fYear
    1991
  • fDate
    3-6 Jun 1991
  • Firstpage
    406
  • Lastpage
    412
  • Abstract
    A method for identifying groups of intensity edges in an image that are likely to result from the same convex object in a scene is described. A key property of the method is that its output is no more complex than the original image. The method uses a triangulation of linear edge segments to define a local neighborhood that is scale invariant. From this local neighborhood a local convexity graph that encodes which neighboring image edges could be part of a convex group of image edges is constructed. A path in the graph corresponds to a convex polygonal chain in the image, such as a convex polygon or a spiral. Examples are presented to illustrate that the technique find intuitively salient groups
  • Keywords
    computational geometry; computer vision; computerised picture processing; convex edge groupings; convex polygonal chain; encoding; intensity edges; linear edge segments; local convexity graph; local neighborhood; scale invariant; triangulation; Computational complexity; Computer science; Filtering; Image recognition; Image segmentation; Jacobian matrices; Layout; Shape; Spirals; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2148-6
  • Type

    conf

  • DOI
    10.1109/CVPR.1991.139724
  • Filename
    139724