• DocumentCode
    2480932
  • Title

    Affine invariant shape descriptors: The ICA-Fourier descriptor and the PCA-Fourier descriptor

  • Author

    Mei, Ye ; Androutsos, Dimitrios

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we propose two new affine invariant shape descriptors, the ICA-Fourier descriptor and the PCA-Fourier descriptor. We tested the descriptors by using them as features for shape based silhouette image retrieval. Experiments on a 1000 silhouette image database show promising retrieval rates of 95.41% and 93.63%, using the ICA-Fourier descriptor and the PCA-Fourier descriptor, respectively. The relationship between those two descriptors are also explained. The proposed PCA-Fourier descriptor is computationally more efficient than its ICA counterpart, while having comparable performance.
  • Keywords
    Fourier transforms; affine transforms; feature extraction; image retrieval; independent component analysis; principal component analysis; ICA-Fourier descriptor; PCA-Fourier descriptor; affine invariant shape descriptor; image database; independent component analysis; principal component analysis; shape based silhouette image retrieval; Computer vision; Fourier transforms; Image databases; Image retrieval; Independent component analysis; Information retrieval; Object recognition; Shape; Testing; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761381
  • Filename
    4761381