• DocumentCode
    3062872
  • Title

    Features invariant to linear transformations in 2D and 3D

  • Author

    Reiss, T.H.

  • Author_Institution
    Dept. of Eng., Cambridge Univ., UK
  • fYear
    1992
  • fDate
    30 Aug-3 Sep 1992
  • Firstpage
    493
  • Lastpage
    496
  • Abstract
    Planar objects can be recognized independent of viewpoint using features invariant to affine transformations. Such features can be generated from the image moments using algebraic invariants. This paper shows how to use tensors to generate algebraic invariants in 2D and 3D, and shows that these features are much more robust than affine invariant Fourier descriptors
  • Keywords
    feature extraction; image recognition; tensors; 2D; 3D; algebraic invariants; features invariant to affine transformations; image moments; planar object recognition; tensors; Polynomials; Robustness; Tensile stress; Transmission line matrix methods; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
  • Conference_Location
    The Hague
  • Print_ISBN
    0-8186-2920-7
  • Type

    conf

  • DOI
    10.1109/ICPR.1992.202032
  • Filename
    202032
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3062872