• DocumentCode
    1742362
  • Title

    Robust detection of skewed symmetries

  • Author

    Shen, Dinggang ; Ip, Heorace H S ; Teoh, Eam Khwang

  • Author_Institution
    Dept. of Radiol., Johns Hopkins Univ., MD, USA
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1010
  • Abstract
    An affine-invariant feature vector, which captures local and semi-local features, has been used in the detection of skewed symmetries. Here, the problem of symmetry axes detection has been formulated as a line detection problem, with known orientations within a local similarity matrix computed for a shape. Moreover, our technique allows all the local reflection-symmetries within an object to be detected. Experiments on detecting skewed symmetries of self-symmetric objects and generalized objects, under noise and occlusions, have demonstrated the effectiveness of this method
  • Keywords
    feature extraction; matrix algebra; symmetry; line detection problem; local similarity matrix; occlusions; robust detection; self-symmetric objects; skewed symmetries; symmetry axes detection; Computer science; Computer vision; Feature extraction; Noise shaping; Object detection; Radiology; Robustness; Sampling methods; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.903716
  • Filename
    903716