• DocumentCode
    1101034
  • Title

    Symmetry as a continuous feature

  • Author

    Zabrodsky, Hagit ; Peleg, Shmuel ; Avnir, David

  • Author_Institution
    Inst. of Comput. Sci., Hebrew Univ., Jerusalem, Israel
  • Volume
    17
  • Issue
    12
  • fYear
    1995
  • fDate
    12/1/1995 12:00:00 AM
  • Firstpage
    1154
  • Lastpage
    1166
  • Abstract
    Symmetry is treated as a continuous feature and a continuous measure of distance from symmetry in shapes is defined. The symmetry distance (SD) of a shape is defined to be the minimum mean squared distance required to move points of the original shape in order to obtain a symmetrical shape. This general definition of a symmetry measure enables a comparison of the “amount” of symmetry of different shapes and the “amount” of different symmetries of a single shape. This measure is applicable to any type of symmetry in any dimension. The symmetry distance gives rise to a method of reconstructing symmetry of occluded shapes. The authors extend the method to deal with symmetries of noisy and fuzzy data. Finally, the authors consider grayscale images as 3D shapes, and use the symmetry distance to find the orientation of symmetric objects from their images, and to find locally symmetric regions in images
  • Keywords
    image processing; symmetry; 3D shapes; continuous measure of distance from symmetry; fuzzy data; grayscale images; noisy data; occluded shapes; symmetrical shape; symmetry distance; Chemical processes; Computer science; Gray-scale; Image reconstruction; Medical diagnosis; Mirrors; Noise shaping; Reflection; Retina; Shape measurement;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.476508
  • Filename
    476508