{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,19]],"date-time":"2024-04-19T19:10:03Z","timestamp":1713553803563},"reference-count":17,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Wavelets Multiresolut Inf. Process."],"published-print":{"date-parts":[[2012,3]]},"abstract":"<jats:p>Texture classification is a challenging and important problem in image analysis. graphical models (GM) are promising tools for texture analysis. In this paper, we address the problem of learning the structure of Gaussian graphical models (GGM) for texture models. GGM can be considered as regression problems due to the connection between the local Markov properties and conditional regression of a Gaussian random variable. We utilize L<jats:sub>1<\/jats:sub>-penalty regularization technique for appropriate neighborhood selection and parameter estimation simultaneously. The proposed algorithms are applied in texture synthesis and classification. Experimental results on Brodatz textures demonstrate that the proposed algorithms have good performance and prospects.<\/jats:p>","DOI":"10.1142\/s0219691312500154","type":"journal-article","created":{"date-parts":[[2012,2,15]],"date-time":"2012-02-15T02:25:24Z","timestamp":1329272724000},"page":"1250015","source":"Crossref","is-referenced-by-count":0,"title":["TEXTURE ANALYSIS USING GAUSSIAN GRAPHICAL MODELS"],"prefix":"10.1142","volume":"10","author":[{"given":"GUAN","family":"YANG","sequence":"first","affiliation":[{"name":"School of Mathematics and Computational Science, Sun Yat-sen University, Guangdong Province Key Laboratory of Computational Science, Guangzhou 510275, China"},{"name":"School of Computer Science, Zhongyuan University of Technology, Zhengzhou 450007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"GUO-CAN","family":"FENG","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computational Science, Sun Yat-sen University, Guangdong Province Key Laboratory of Computational Science, Guangzhou 510275, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZHI-HONG","family":"LUO","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510275, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZHI-YONG","family":"LIU","sequence":"additional","affiliation":[{"name":"Industry Center, Shenzhen Polytechnic, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2012,5]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1973.4309314"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219691311004055"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1109\/TASSP.1985.1164641"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1049\/ip-vis:19971182"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1142\/S0219691310003468"},{"key":"rf6","doi-asserted-by":"publisher","DOI":"10.1142\/S0219691309002854"},{"key":"rf7","first-page":"661","volume":"12","author":"Liu X.","journal-title":"IEEE Trans. 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