• DocumentCode
    2538188
  • Title

    Shocks from images: propagation of orientation elements

  • Author

    Tek, Hüseyin ; Stoll, Perry A. ; Kimia, Benjamin B.

  • Author_Institution
    Div. of Eng., Brown Univ., Providence, RI, USA
  • fYear
    1997
  • fDate
    17-19 Jun 1997
  • Firstpage
    839
  • Lastpage
    845
  • Abstract
    The extraction of figure symmetry from image contours faces a number of fundamental difficulties: object symmetries are distorted due to (i) gaps in the bounding contour of a shape due to figure-ground blending, weak contrast edges, highlights, noise, etc.; (ii) an introduction of parts and occluders, and (iii) spurious edge elements due to surface markings, texture, etc. A framework for extracting such symmetries from real images is proposed based on the propagation of contour orientation information and the detection of four types of singularities (shocks) arising from the collision of propagating elements. In this paper, we show that an additional labeling of shocks based on whether the colliding wavefronts carry true orientation information (regular vs. rarefaction waves) allows a division of shocks into three sets: regular shocks are the partial shocks of partial contours as they remain invariant to the completion of the contour; semi-degenerate and degenerate shocks depict potential parts and gaps. Finally, shocks altered due to spurious edges, occlusion, and gaps are recovered via a simulation of inter-penetrating waves generated at select shock groups which with the aid of the above shock labels leads to second and further generations of shocks
  • Keywords
    edge detection; feature extraction; image segmentation; colliding wavefronts; edge elements; figure symmetry; image contours; object symmetries; orientation elements; real images; Background noise; Data mining; Electric shock; Labeling; Noise figure; Noise generators; Noise measurement; Noise shaping; Shape; Surface texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
  • Conference_Location
    San Juan
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7822-4
  • Type

    conf

  • DOI
    10.1109/CVPR.1997.609425
  • Filename
    609425