• DocumentCode
    1620992
  • Title

    Shape matching of 3D contours using normalized Fourier descriptors

  • Author

    Zhang, Hao ; Fiume, Eugene

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Toronto, Ont., Canada
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    261
  • Lastpage
    268
  • Abstract
    In this paper, we develop a simple, eigenspace matching algorithm for closed 3D contours. Our algorithm relies on a novel method which normalizes the Fourier descriptors (FDs) of a 3D contour with respect to two of its FD coefficients corresponding to the lowest non-zero frequencies. The remaining matching task only involves vertex shift and rotation about the z-axis. Our approach is inspired by the observation that the traditional Fourier transform of a 1D signal is equivalent to the decomposition of the signal into a linear combination of the eigenvectors of a smoothing operator. It turns out that our FD normalization is equivalent to aligning the limit plane approached by the sequence of progressively smoothed 3D contours with the xy-plane
  • Keywords
    Fourier transforms; computational geometry; computer vision; edge detection; eigenvalues and eigenfunctions; image matching; stereo image processing; closed 3D contours; eigenspace matching algorithm; eigenvectors; lowest nonzero frequencies; normalization; normalized Fourier descriptors; progressively smoothed 3D contour; shape matching; smoothing operator; vertex rotation; vertex shift; z-axis; Computer science; Computer vision; Educational institutions; Electronic mail; Fourier transforms; Frequency; Image edge detection; Object recognition; Shape measurement; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Shape Modeling International, 2002. Proceedings
  • Conference_Location
    Banff, Alta.
  • Print_ISBN
    0-7695-1546-0
  • Type

    conf

  • DOI
    10.1109/SMI.2002.1003554
  • Filename
    1003554