Iris identification using the Pram neural network

Abstract

In this paper we propose a new approach to performer is identification. In contrast to existing approaches that consider the Hamming distance measure to perform identification, the new approach considers the addition of a well trained neural network to identify the iris. The disadvantage of previous schemes is the difficulty to deal with the variability of irises within the same iris class due to noise and movement of the eye as well as difficulties in capturing a clear image of the eye, which makes the choice of threshold values to identify the class to which belong the iris a difficult and a time consuming task. The new approach is based on a digital neural network pRAM.