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This paper presents a new method for rotation invariant texture classification based on the circular Gabor wavelets. A circular Gabor filter bank is proposed to decompose an image into multiple scales and be rotation invariant. By the mean and variance of the circular Gabor filtered image, a discriminant can be found to classify rotated images. In the primary experiments, comparatively high correct classification rates were obtained using a large test sample set.

Rotation Invariant Texture Classification Using Circular Gabor Filter Banks