Yambay, D; Walczak, B; Schuckers, S; Czajka, A
Presentation attacks such as printed iris images or patterned contact lenses can be used to circumvent an iris recognition system. Different solutions have been proposed to counteract this vulnerability with Presentation Attack Detection (commonly called liveness detection) being used to detect the presence of an attack, yet independent evaluations and comparisons are rare. To fill this gap we have launched the first international iris liveness competition in 2013. This paper presents detailed results of its second edition, organized in 2015 (LivDet-Iris 2015). Four software-based approaches to Presentation Attack Detection were submitted. Results were tallied across three different iris datasets using a standardized testing protocol and large quantities of live and spoof iris images. The Federico Algorithm received the best results with a rate of rejected live samples of 1.68% and rate of accepted spoof samples of 5.48%. This shows that simple static attacks based on paper printouts and printed contact lenses are still challenging to be recognized purely by software-based approaches. Similar to the 2013 edition, printed iris images were easier to be differentiated from live images in comparison to patterned contact lenses.