A Review on Iris Recognition Techniques

Abstract

Identify and verify the features of Iris is basically a method of extracting biometric graphical patterns over the images of irises of human’s eyes that contains complex patterns which are unique, stable. Iris is the most chosen method of biometric in comparison to the other available methods due to its features that have exclusivity, constancy. Nevertheless, tainted pictures of iris confined under less-constrained acquisition setups. Previously developed systems are often based on deprived edge recognition approaches and filters. The majority of techniques employed basic algorithms available for the operations needs to take place for the recognition of Iris. Distinctive actions executed to identify an iris are the methods of segmentation, normalization, feature extraction and matching. Canny Edge detection, Hough Transform, Gabor Filter, Daugman’s operator are some frequently used techniques in the field of Iris recognition. There are few limitations as complex computational approach, lack of accuracy for complex noisy image, obstructions due to lens, eye lashes and reflection examined in the prior work done. So, a system is required which can efficiently recognize the Iris with zero false rates and secure the crucial applications. This paper reviews previously proposed systems that employed with various feature recognition techniques where precision level is distinct.