Rotation-invariant texture characterization using isotropic wavelet frames

Deals with the extraction of rotation-invariant texture features from multiscale image decomposition. We argue that the often used separable filtering schemes are very impractical for rotation-invariant feature extraction. Therefore we propose a scheme based on non-separable isotropic wavelet frames. The performance of the features is evaluated in a classification experiment.

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