An integrated framework for image classification
نویسندگان
چکیده
This paper presents a novel method for classifying an image into one of predeened classes in a data bank by applying mutual information to a representation of the Fourier amplitude domain. Template and test images are made translation and rotation invariant through the Fourier-Mellin transform. While mutual information could be employed here, we choose instead to apply it to the lower dimension phase spectrum generated by the complex multireso-lution wreath product transform of the Fourier-Mellin amplitude spectrum. The phase information of this transform adequately preserves edges even at lower resolutions while permitting at the same time, a reduction in the computational burden. Brodatz textures and ORL faces are used to demonstrate the capability of this algorithm.
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