Iris Recognition: An analysis using LBP, SVC and Distance metrics

Abstract

Abstract In this paper, experiment has been conducted to find the optimum iris recognition system between the combinations Local Binary Pattern (LBP) and Distance metric, and LBP and Linear Support Vector Classifier (SVC). First, experiment has been conducted using LBP and different distance metrics. For each of the distance metric, the FAR, FRR and accuracy have been calculated for different threshold values. From the obtained result, it has been found that cityblock distance gives better accuracy compared to remaining distance metrics and the accuracy obtained is 65.93% on CASIA iris dataset. Secondly, iris recognition has been carried out using Local Binary Pattern (LBP) and Linear Support Vector Classifier (SVC). The combination of LBP and Linear SVC is giving an accuracy of 91.83% on CASIA iris dataset.