"RIV/67985556:_____/08:00317591" . "texture segmentation; image segmentation; benchmark"@en . "399769" . . "Texture Segmentation Benchmark"@en . "The Prague texture segmentation data-generator and benchmark is a web based ( http://mosaic.utia.cas.cz) service designed to mutually compare and rank different texture segmenters, and to support new segmentation and classification methods development. The benchmark verifies their performance characteristics on monospectral, multispectral, bidirectional texture function (BTF) data and enables to test their noise robustness, scale, and rotation or illumination invariance. It can easily be used for other applications such as feature selection, image compression, and query by pictorial example, etc. The benchmark functionalities are demonstrated on five previously published image segmentation algorithms evaluation."@en . . "978-1-4244-2174-9" . "Haindl, Michal" . . . . "Texture Segmentation Benchmark"@en . "RIV/67985556:_____/08:00317591!RIV10-MSM-67985556" . . "Los Alamitos" . "Texture Segmentation Benchmark" . . . . . . "IEEE Press" . . "Proceedings of the 19th International Conference on Pattern Recognition" . . "Texture Segmentation Benchmark" . . . "Mike\u0161, Stanislav" . . . "2008-12-07+01:00"^^ . "2"^^ . "Tampa" . . "2"^^ . "P(1ET400750407), P(1M0572), P(GA102/07/1594), P(GA102/08/0593), Z(AV0Z10750506)" . . . "[45C03DBB5B9D]" . . "The Prague texture segmentation data-generator and benchmark is a web based ( http://mosaic.utia.cas.cz) service designed to mutually compare and rank different texture segmenters, and to support new segmentation and classification methods development. The benchmark verifies their performance characteristics on monospectral, multispectral, bidirectional texture function (BTF) data and enables to test their noise robustness, scale, and rotation or illumination invariance. It can easily be used for other applications such as feature selection, image compression, and query by pictorial example, etc. The benchmark functionalities are demonstrated on five previously published image segmentation algorithms evaluation." . "4"^^ . .