0431524 20240103204613.620141021235959.9 84919934811 000359818003017 10.1109/ICPR.2014.513 6 s. P cav_un_epca*0431131978-1-4799-5208-31051-46512972-2977StockholmIEEE Computer Society2014 noisy images histogram similarity cav_un_auth*0282545 Höschl Cyril UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101087 Flusser Jan UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2014/ZOI/hoschl-0431524.pdf cav_un_auth*0292734 GA13-29225S GA ČR We present a content-based image retrieval method which is particularly designed for noisy images. The images are retrieved according to histogram similarity. To reach high robustness to noise, the histograms are described by novel features which are insensitive to convolution with a Gaussian kernel, i.e. insensitive to a Gaussian additive noise in original images. The advantage of the new method is demonstrated experimentally on real data. cav_un_auth*0306095 22nd International Conference on Pattern Recognition 22.08.2014-28.08.2014 Stockholm SE JD 20000 20200 20206 2015 2 PR RVO:67985556 http://hdl.handle.net/11104/0237643 S RIV/67985556:_____/14:00431524!RIV15-AV0-67985556 152459976 Doplnění UT WOS a Scopus RIV/67985556:_____/14:00431524!RIV15-GA0-67985556 152501036 Doplnění UT WOS a Scopus 50 0.293 11.42 0.77 Q3 2014 84919934811 SCOPUS 000359818003017 WOS cav_un_epca*0431131 Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014) 978-1-4799-5208-3 1051-4651 2972 2977 Stockholm IEEE Computer Society 2014