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SUMMARYThis paper proposes a method in which the amplitude and phase information of a two-dimensional Gabor filter output are utilized in the supervised segmentation of texture images. The segmentation procedure is as follows. The amplitude and the phase difference between adjacent pixels of the multiple filter outputs are used as the feature parameters. By applying maximum-likelihood estimation of each pixel in the test image, it is decided to which supervised image the pixel belongs. Then, based on the result of segmentation, maximum a posteriori probability estimation is iteratively applied and the final result of segmentation with region integration is obtained. It is shown that when the number of filters in the frequency space is smaller, the phase difference feature parameter contains information which cannot be obtained by using only the amplitude feature parameter. In particular, it is experimentally shown to be effective to weight the phase difference feature parameters by the amplitude. The accuracy of segmentation can be improved by thus combining the phase difference with the amplitude feature parameter.

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