Authors : Bineet Kaur, Sukhwinder Singh and Jagdish Kumar
Abstract: Human iris recognition is the most promising field of biometrics for reliable user identification. Human iris contains a unique textural pattern which remains stable throughout lifetime. This makes it the most desirable biometric modality. However, iris pattern is obfuscated by various covariates like textured contact lenses and printed iris images that result in iris spoofing where an imposter impersonates the genuine enrolled user. This poses a great challenge in iris recognition when used in large-scale applications. The study presents a detailed study on the effect of iris spoofing via. textured contact lenses and print attacks on iris recognition performance. Various researchers have proposed algorithms for the detection of fake and genuine iris samples in order to reduce iris spoofing attacks. However, there is a need to provide more generalized algorithms for detection of unpredictable spoofing attacks, so that, the system is secure, computationally efficient and accurate.
Bineet Kaur, Sukhwinder Singh and Jagdish Kumar, 2018. A Study on Fake Iris Detection under Spoofing Attacks. Journal of Engineering and Applied Sciences, 13: 2049-2056.