0459179 20240103212213.920160506235959.9 84962097630 000376708000010 10.1016/j.patcog.2016.03.003 A competition in unsupervised color image segmentation 16 s. P cav_un_epca*02573880031-3203Pattern Recognition579 (2016)136-151Elsevier Unsupervised image segmentation Segmentation contest Texture analysis cav_un_auth*0101093 Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Haindl Michal UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101165 Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Mikeš Stanislav UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2016/RO/haindl-0459179.pdf cav_un_auth*0303439 GA14-10911S GA ČR CZ A competition in unsupervised color image segmentation took place in conjunction with the 22nd International Conference on Pattern Recognition (ICPR 2014). It aimed to promote evaluation of unsupervised color image segmentation algorithms using publicly available data sets, and to allow for any subsequent methods to be easily evaluated and compared with the results of the contested methods under identical conditions. Our comparison of different methods is based on the standard methodology of performance assessment using an on-line verification server. We present in this paper the evaluation of the top six results submitted to the ICPR 2014 contest in unsupervised color image segmentation and compare them with 11 other state-of-the-art unsupervised image segmenters. BD 2017 2 4 A hod 4ah 20231122141653.7 RVO:67985556 http://hdl.handle.net/11104/0259701 1 Department of Pattern Recognition UTIA-B 10201 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE S 2 Article Computer Science Artificial Intelligence|Engineering Electrical Electronic ENGINEERING.ELECTRICAL&ELECTRONIC|COMPUTERSCIENCE.ARTIFICIALINTELLIGENCE 4.991 0.913 8.7 0.0297 1.361 23919 1.501 Q1 4.146 320 Q1 85.445 90.3 Q1 Q1 91.412 2016 Soubory v repozitáři: haindl-0459179.pdf 84962097630 SCOPUS 000376708000010 WOS cav_un_epca*0257388 Pattern Recognition 0031-3203 1873-5142 Roč. 57 č. 9 2016 136 151 Elsevier