18 October 2005 Unsupervised texture segmentation using matched Gabor filters
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Abstract
A simple and fast multi-channel filtering algorithm is presented in the paper for texture segmentation. This algorithm requires only a small number of channels and automatically determines the channel parameters by analysis of the Fourier power spectrum. Also it does not need a priori knowledge about the type and number of textures occurring in the input images. We can gain categories number by the square-error plot of different clusters. It does not involve any human intervention. The algorithm is tested extensively with a variety of Brodatz's textures and real textures. The segmentation results validate the practicability of this algorithm.
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Haiyang Wang, Yan Bai, Xiaoyu Zhang, Delu Pan, "Unsupervised texture segmentation using matched Gabor filters", Proc. SPIE 5982, Image and Signal Processing for Remote Sensing XI, 59821D (18 October 2005); doi: 10.1117/12.627408; https://doi.org/10.1117/12.627408
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