Iris Recognition Based on Unique Iris Templates for Reliable Personal Authentication

摘要

The automatic recognition of an individual using the exclusive biometric trait like iris is the latest sensation in the field of biometric applications. The enormous mathematical advantages provided by iris pattern recognition make it hugely popular amongst the real time commercial applications which involve large scale databases. In recent years, we have witnessed several newly proposed methods attracting a lot of attention in the biometrics literature. Most of these methods basically use Daugman's algorithm with a slight variation and claim to be very promising in terms of efficiency. However, there has been barely any effort to ensure the uniqueness of iris pattern and account for the rotational inconsistencies present in the iris images while capturing them. After analyzing the recently developed frameworks, the authors of this paper have proposed an unaccustomed approach which considers these aspects which are usually neglected in the methods proposed so far. This paper gives an insight of our system designed by a novel approach and presents the performance achieved by it over two standard iris image datasets of IIT Delhi and CASIA1. Our approach outperforms the well-known existing methods over these two different datasets on the basis of experimental results obtained. Moreover, it is illustrated that we have significantly reduced both the FAR and FRR at a unique separation point which is a remarkable accolade in this field. We have almost achieved perfect recognition with FAR and FRR of 0.001% and 0.069% respectively over the IIT Delhi and CASIA1 dataset.