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Modeling and Classifying Symmetries Using a Multiscale Opponent Color Representation
November 1998 (vol. 20 no. 11)
pp. 1224-1235

Abstract—A new class of multiscale symmetry features provides a useful high-level representation for color texture. These symmetry features are defined within and between the bands of a color image using complex moments computed from the output of a bank of orientation and scale selective filters. We show that these features not only represent symmetry information but are also invariant to rotation, scale, and illumination conditions. The features computed between color bands are motivated by opponent process mechanisms in human vision. Experimental results are provided to show the performance of this set of features for texture classification and retrieval.

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Index Terms:
Symmetry, Gabor filter, opponent, multiscale, color, texture, recognition, opponent color, image retrieval.
Citation:
Bea Thai, Glenn Healey, "Modeling and Classifying Symmetries Using a Multiscale Opponent Color Representation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 11, pp. 1224-1235, Nov. 1998, doi:10.1109/34.730556
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