Extracting symmetry features from color images

We develop methods to extract semantically meaningful symmetries from color images. These symmetries are defined within and between color bands using complex moments computed from the output of a bank of orientation and scale selective filters. From this representation, we derive a set of features which are invariant to rotation, scale, and illumination conditions. Experimental results are provided to show the performance of this set of features for classification and image database partitioning.

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