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Texture image segmentation based on M-Band Wavelet derived features using Fuzzy C-Means

This paper presents a scheme for segmentation of texture images combining M-band wavelet transform and Fuzzy C-Means. M-band wavelet transform yields a large number of sub images which enhances the performance. M-Band Wavelet transform decomposes an image in to M×M channels. Different combinations of these band pass sections produce various scales and orientations in frequency plane, hence it produces a sixteen sub-band images. These features are subjected to Fuzzy C-Means clustering technique for segmentation. The advantage of FCM is that it does not require a priori knowledge to segment a region. This new combined algorithm produces good segmentation results by applying FCM for M-Band Wavelet extracted features.