Biometric Authentication using Nonparametric Methods

TL;DR

This paper presents a biometric authentication system utilizing nonparametric methods on iris and signature data, emphasizing minimal feature extraction, variance analysis, and classifier performance to achieve high accuracy and computational efficiency.

Contribution

It introduces a novel approach combining variance-based segmentation, Hu moments, and nonparametric classifiers for biometric authentication with reduced computational load.

Findings

High accuracy in iris authentication with zero FAR for most subjects.

Achieved 8.13% FRR and 10% FAR in signature verification.

Reduced feature set leads to faster, simpler biometric systems.

Abstract

The physiological and behavioral trait is employed to develop biometric authentication systems. The proposed work deals with the authentication of iris and signature based on minimum variance criteria. The iris patterns are preprocessed based on area of the connected components. The segmented image used for authentication consists of the region with large variations in the gray level values. The image region is split into quadtree components. The components with minimum variance are determined from the training samples. Hu moments are applied on the components. The summation of moment values corresponding to minimum variance components are provided as input vector to k-means and fuzzy k-means classifiers. The best performance was obtained for MMU database consisting of 45 subjects. The number of subjects with zero False Rejection Rate [FRR] was 44 and number of subjects with zero False Acceptance Rate [FAR] was 45. This paper addresses the computational load reduction in off-line signature verification based on minimal features using k-means, fuzzy k-means, k-nn, fuzzy k-nn and novel average-max approaches. FRR of 8.13% and FAR of 10% was achieved using k-nn classifier. The signature is a biometric, where variations in a genuine case, is a natural expectation. In the genuine signature, certain parts of signature vary from one instance to another. The system aims to provide simple, fast and robust system using less number of features when compared to state of art works.