• DocumentCode
    2325929
  • Title

    Affine integral invariants and matching of curves

  • Author

    Sato, Jun ; Cipolla, Roberto

  • Author_Institution
    Dept. of Eng., Cambridge Univ., UK
  • Volume
    1
  • fYear
    1996
  • fDate
    25-29 Aug 1996
  • Firstpage
    915
  • Abstract
    We propose integral invariants based on a group invariant parameterisation. These new invariants do not suffer from the occlusion problem, do not require any correspondence of image features unlike algebraic invariants, and are less sensitive to noise than differential invariants. Affine differential geometry is applied to this framework, and novel affine integral invariants are derived. A quasi-invariant parameterisation enables us to reduce the order of derivatives required. The proposed invariants are applied for extracting corresponding contour curves of natural images. The noise sensitivity of the proposed invariants is compared with that of differential invariants
  • Keywords
    Lie groups; computer vision; differential geometry; group theory; image sequences; integral equations; affine differential geometry; affine integral invariants; contour curves; curves matching; differential invariants; group invariant parameterisation; natural images; noise sensitivity; quasi-invariant parameterisation; Computer vision; Geometry; Image segmentation; Image sequences; Layout; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1996., Proceedings of the 13th International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-7282-X
  • Type

    conf

  • DOI
    10.1109/ICPR.1996.546157
  • Filename
    546157