Efficient Gabor filter design for texture segmentation Export

@article{citeulike:278187, abstract = {Gabor filters have been successfully applied to a broad range of image processing tasks. The present paper considers the design of a single filter to segment a two-texture image. A new efficient algorithm for Gabor-filter design is presented, along with methods for estimating filter output statistics. The algorithm draws upon previous results that showed that the output of a Gabor-filtered texture is modeled well by a Rician distribution. A measure of the total output power is used to select the center frequency of the filter and is used to estimate the Rician statistics of the Gabor-filtered image. The method is further generalized to include the statistics of postfiltered outputs that are generated by a Gaussian filtering operation following the Gabor filter. The new method typically requires an order of magnitude less computation to design a filter than a previously proposed method. Experimental results demonstrate the efficacy of the method.}, author = {Weldon, Thomas P. and Higgins, William E. and Dunn, Dennis F.}, citeulike-article-id = {278187}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S0031-3203(96)00047-7}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6V14-3VTK1KR-6/2/8a6fbd7398bae2ae29d688cdad007b35}, doi = {10.1016/S0031-3203(96)00047-7}, journal = {Pattern Recognition}, keywords = {ee520, filtering, segmentation, texture}, month = {December}, number = {12}, pages = {2005--2015}, posted-at = {2005-10-18 04:15:52}, priority = {2}, title = {Efficient Gabor filter design for texture segmentation}, url = {http://dx.doi.org/10.1016/S0031-3203(96)00047-7}, volume = {29}, year = {1996} }

TY - JOUR ID - citeulike:278187 L3 - citeulike-article-id:278187 N2 - Gabor filters have been successfully applied to a broad range of image processing tasks. The present paper considers the design of a single filter to segment a two-texture image. A new efficient algorithm for Gabor-filter design is presented, along with methods for estimating filter output statistics. The algorithm draws upon previous results that showed that the output of a Gabor-filtered texture is modeled well by a Rician distribution. A measure of the total output power is used to select the center frequency of the filter and is used to estimate the Rician statistics of the Gabor-filtered image. The method is further generalized to include the statistics of postfiltered outputs that are generated by a Gaussian filtering operation following the Gabor filter. The new method typically requires an order of magnitude less computation to design a filter than a previously proposed method. Experimental results demonstrate the efficacy of the method. IS - 12 JF - Pattern Recognition EP - 2015 TI - Efficient Gabor filter design for texture segmentation VL - 29 SP - 2005 KW - ee520 KW - filtering KW - segmentation KW - texture AU - Weldon, Thomas AU - Higgins, William AU - Dunn, Dennis PY - 1996/12// UR - http://dx.doi.org/10.1016/S0031-3203(96)00047-7 ER -