0343253 20240111140739.920100617235959.9 4 s. www cav_un_epca*0343250978-1-4244-7166-9578-581Los AlamitosIEEE2010 Texture modeling Bernoulli mixture EM algorithm cav_un_auth*0101093 Haindl Michal Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101100 Havlíček Vojtěch Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101091 Grim Jiří Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. pdf http://library.utia.cas.cz/separaty/2010/RO/haindl-colour texture representation based on multivariate bernoulli mixtures.pdf 1M0572 GA MŠk cav_un_auth*0001814 2C06019 GA MŠk CZ cav_un_auth*0216518 GA102/08/0593 GA ČR cav_un_auth*0239567 CEZ:AV0Z10750506 A novel generative colour texture model based on multivariate Bernoulli mixtures is proposed. A measured multispectral texture is spectrally factorised and multivariate Bernoulli mixtures are further learned from single bit planes of the orthogonal monospectral components and used to synthesise and enlarge these monospectral binary factor components. Texture synthesis is based on easy computation of arbitrary conditional distributions from the model. Finally single synthesised monospectral texture bit planes are transformed into the required synthetic multispectral texture. This model can easily serve not only for texture enlargement but also for segmentation, restoration, and retrieval or to model single factors in complex Bidirectional Texture Function (BTF) space models. The strengths and weaknesses of the presented Bernoulli mixture based approach are demonstrated on several colour texture examples. cav_un_auth*0262028 10th International Conference on Information Sciences, Signal Processing and their Applications Kuala Lumpur 10.05.2010-13.05.2010 MY 2011 BD http://hdl.handle.net/11104/0185771 2010 pdf cav_un_epca*0343250 10th International Conference on Information Sciences, Signal Processing and their Applications 978-1-4244-7166-9 578 581 Los Alamitos IEEE 2010