Title :
Features invariant to linear transformations in 2D and 3D
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
fDate :
30 Aug-3 Sep 1992
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;
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
DOI :
10.1109/ICPR.1992.202032
