The Performance Enhancement Systems of Human Iris Pattern and Recognition Method through Digital Authentication Application

Abstract

Human iris and recognition patterns have been recognized as the best biometric marking ever found, owing to the uniqueness of iris and the textured iris patterns tend to remain natural, unchangeable and recognizable through existence. Mathematical analyses of the special stable patterns formed within the iris include Iris detection methods and a comparative analysis is carried out utilizing an established database. In this document, a clean electoral system is created to build a fraud-free ID list of electors. To find the Iris and Eyes, the algorithm of canny edge detection is used, Dougman's normalization procedure is used, object filters are added and finally the corresponding process is conducted for the Euclidian set. Biometric authentication confirms our identification by being a simple and increasingly secure method. We implement a weighted, majority voting process for all biometric authentication systems utilizing a bit wise contrast between inscription and biometric models to resolve this problem and to enable Iris identification in less than ideal images. We also observed that the approach outdoes the current majority and efficient bit sorting strategies through a set of tests with the database CASIA iris.  Our approach is an easy and efficient way to boost the accuracy of established iris detection systems.