Unsupervised texture segmentation using Gabor filters Export

@inproceedings{citeulike:3084873, abstract = {A texture segmentation algorithm inspired by the multichannel filtering theory for visual information processing in the early stages of the human visual system is presented. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatial-frequency domain. A systematic filter selection scheme based on reconstruction of the input image from the filtered images is proposed. Texture features are obtained by subjecting each (selected) filtered image to a nonlinear transformation and computing a measure of energy in a window around each pixel. An unsupervised square-error clustering algorithm is then used to integrate the feature images and produce a segmentation. A simple procedure to incorporate spatial adjacency information in the clustering process is proposed. Experiments on images with natural textures as well as artificial textures with identical second and third-order statistics are reported. The algorithm appears to perform as predicted by preattentive texture discrimination by a human}, author = {Jain, A. K. and Farrokhnia, F.}, booktitle = {Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on}, citeulike-article-id = {3084873}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICSMC.1990.142050}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=142050}, doi = {10.1109/ICSMC.1990.142050}, journal = {Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on}, keywords = {ban, filters, gabor, segmentation, texture}, pages = {14--19}, posted-at = {2008-08-05 11:43:42}, priority = {5}, title = {Unsupervised texture segmentation using Gabor filters}, url = {http://dx.doi.org/10.1109/ICSMC.1990.142050}, year = {1990} }

TY - CONF ID - citeulike:3084873 L3 - citeulike-article-id:3084873 N2 - A texture segmentation algorithm inspired by the multichannel filtering theory for visual information processing in the early stages of the human visual system is presented. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatial-frequency domain. A systematic filter selection scheme based on reconstruction of the input image from the filtered images is proposed. Texture features are obtained by subjecting each (selected) filtered image to a nonlinear transformation and computing a measure of energy in a window around each pixel. An unsupervised square-error clustering algorithm is then used to integrate the feature images and produce a segmentation. A simple procedure to incorporate spatial adjacency information in the clustering process is proposed. Experiments on images with natural textures as well as artificial textures with identical second and third-order statistics are reported. The algorithm appears to perform as predicted by preattentive texture discrimination by a human JF - Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on EP - 19 TI - Unsupervised texture segmentation using Gabor filters T2 - Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on SP - 14 KW - ban KW - filters KW - gabor KW - segmentation KW - texture AU - Jain, AK AU - Farrokhnia, F PY - 1990/// UR - http://dx.doi.org/10.1109/ICSMC.1990.142050 ER -