Impact of segmentation on iris liveness detection

Abstract

Applying iris recognition systems in many sensitive security areas highlights the importance of developing liveness detection methods. These methods read the users physiological signs of life to verify if the iris pattern acquired for identification is fake or real. This paper explores the results of BSIF for solving the problem of iris liveness detection to combat presentation attacks. Four public datasets representing printed, plastic, synthetic and contact lens attacks were used for method evaluation in both scenarios segmented and unsegmented eye images. The results have showed that BSIF can efficiently detect plastic and synthetic attacks without segmentation with correct classification rate of 100%. In addition, unsegmented eye images achieved better results in detecting print attack on the tested datasets. While, segmentation is still required in the most challenging attack which is by contact lens.