• DocumentCode
    2689555
  • Title

    An Affine Resilient Curvature Scale-Space Corner Detector

  • Author

    Awrangjeb, Mohammad ; Guojun Lu ; Murshed, Manzur

  • Author_Institution
    Gippsland Sch. of Inf. Technol., Monash Univ., Clayton, Vic., Australia
  • Volume
    1
  • fYear
    2007
  • fDate
    15-20 April 2007
  • Abstract
    Curvature scale-space (CSS) corner detectors look for curvature maxima or inflection points on planar curves. They use arc-length parameterized curvature. Therefore, they are not robust to affine transformations since the arc-length of a curve is not preserved under affine transformations. However, the affine-length of a curve is relatively invariant to affine transformations. This paper presents an improved CSS corner detector by applying the affine-length parameterized curvature to the CSS corner detection technique. A thorough robustness study has been carried out on a large database considering a wide range of affine transformations.
  • Keywords
    feature extraction; image matching; affine transformations; arc-length parameterized curvature; resilient curvature scale-space corner detector; Australia; Cascading style sheets; Databases; Detectors; Image edge detection; Information technology; Kernel; Object detection; Robustness; Shape; Corner detection; curvature scale-space;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0727-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2007.366137
  • Filename
    4217309