An Adaptive Approach for Texture Segmentation by Multi-channel Wavelet Frames

We introduce an adaptive approach for texture feature extraction based on multi-channel wavelet frames and two-dimensional envelope detection. Representations obtained from both standard wavelets and wavelet packets are evaluated for reliable texture segmentation. Algorithms for envelope detection based on edge detection and the Hilbert transform are presented. Analytic lters are selected for each technique based on performance evaluation. A K-means clustering algorithm was used to test the performance of each representation feature set. Experimental results for both natural textures and synthetic textures are shown. 1