0089873 20240103184758.520071121235959.9 8 s. cav_un_epca*0089872978-3-540-75174-8244-51BerlinSpringer2007KurzynskiMarek Image identification Image database Decision tree Invariant frame cav_un_auth*0213250 Horáček Ondřej UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0230860 Bican Jakub UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0213251 Kamenický Jan UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101087 Flusser Jan UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2007/zoi/horacek-image retrieval for image theft detection.pdf 1M0572 GA MŠk cav_un_auth*0001814 CEZ:AV0Z10750506 Image retrieval deals with a problem of finding similar pictures in image database. Our task is to find originals of modified images, typically stolen and republished on the web. Our problem is specific in terms of the database size (millions of photos), demanded speed of the search (seconds), and unknown image modifications (loss of quality, radiometric degradation, crop, etc.). Proposed method works in the following tree steps: 1. Image preprocess -- normalization for robustness to the modifications. 2. Retrieval of candidates from the database index -- stochastic decision in each vertex of the index tree is used to find the most relevant candidates. 3. Verification of the candidates -- modified phase correlation is used. The method was implemented in practice with very good results. Based on wide experiments, it was shown that the success rate of the search depends on the level of image modification. Image retreval pro detekci krádeží snímků cav_un_auth*0232818 Computer Recognition Systems Wroclaw 22.10.2007-15.10.2007 PL 2008 BD http://hdl.handle.net/11104/0150937 2007 cav_un_epca*0089872 Computer Recognition Systems 2 978-3-540-75174-8 44 51 Berlin Springer 2007 Advances in Soft Computing 45 Kurzynski Marek 340