Iris Recognition System Using Integro Differential Model & Convolution Neural Networks

Abstract

Authorizing someone has become a substantial need in today's world.. In such circumstances, the integration of artificial intelligence into biometric systems has changed the way people lived and operated at various stages of their lives. Identifying a person basically works in two ways: characteristic or behavioral traits, like palmprint, earprint, iris, face & fingerprint etc. In this paper ,we have worked on Iris based Recognition System as it is one of the most reliable & secure biometric. In our work we have proposed modified segmentation technique(DaughmanIntegroDifferential) and efficient Convolution Neural Network (CNN) structure. We performed our experiments on CASIA iris database Version 1(v-1) consisting of 756 images in 108 folders having 7 images each and have obtained an accuracy of 98%.