• DocumentCode
    2908833
  • Title

    Bispectrum-based feature of 2D and 3D images invariant to similarity transformations

  • Author

    Horikawa, Yo

  • Author_Institution
    Fac. of Educ., Kagawa Univ., Takamatsu, Japan
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    511
  • Abstract
    A novel feature of 2D and 3D images invariant to similarity transformations is derived from the bispectrum. The invariant feature represents the amount of the triplets of the sinusoids with the frequency components consisting of the apexes of similar triangles. An effective method of calculating the invariant feature is also presented. Computer simulation on sinusoidal patterns of different phases and texture images shows that the invariant feature is applicable to the recognition of images suffering from shift and rotation in arbitrary degree, scaling up to double, and additive noise
  • Keywords
    image recognition; 2D images; 3D images; additive noise; bispectrum-based feature; image recognition; rotation invariance; scale invariance; shift invariance; similarity transformations; sinusoid triplets; texture images; Additive noise; Computer simulation; Fourier transforms; Frequency; Image recognition; Noise robustness; Pattern recognition; Phase noise; Pixel; Testing;
  • 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.2000.906124
  • Filename
    906124