0397243 20240103203058.720140124235959.9 000336080600044 10.1109/BTAS.2013.6712729 6 s. C cav_un_epca*0424323978-1-4799-0527-01-6PiscatawayIEEE2013 iris recognition iris occlusion 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*0292156 Krupička Mikuláš Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/RO/haindl-0397243.pdf GAP103/11/0335 GA ČR cav_un_auth*0273627 GA102/08/0593 GA ČR cav_un_auth*0239567 The prerequisite for the accurate iris recognition is to detect all iris occlusions which would otherwise confuse a recognition method and impair its recognition rate. This paper presents a fast multispectral eyelid, eyelash, and reflection detection method based on the underlying three-dimensional spatial probabilistic textural model. The model first adaptively learns its parameters on the flawless iris texture part and subsequently checks for non iris occlusions using the recursive prediction analysis. We provide colour iris occlusion detection results that indicate the advantages of the proposed method and compare it with 97 recent Noisy Iris Challenge Evaluation algorithms. cav_un_auth*0294813 The IEEE Sixth International Conference on Biometrics: Theory, Applications, and Systems (BTAS 2013) Washington DC 29.09.2013-02.10.2013 US 2014 BD 2 RVO:67985556 http://hdl.handle.net/11104/0225895 2013 000336080600044 WOS cav_un_epca*0424323 Biometrics: Theory, Applications and Systems (BTAS), 2013 978-1-4799-0527-0 1 6 Piscataway IEEE 2013