An Improved Biometric Fusion System of Fingerprint and Face using Whale Optimization

Tajinder Kumar,Surender Jangra,Shashi Bhushan

doi:10.14569/ijacsa.2021.0120176

Tajinder Kumar, Surender Jangra + Show 1 more

Open Access

https://doi.org/10.14569/ijacsa.2021.0120176

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Abstract

In the field of wireless multimedia authentication unimodal biometric model is commonly used but it suffers from spoofing and limited accuracy. The present work pro-poses the fusion of features of face and fingerprint recognition system as an Improved Biometric Fusion System (IBFS) leads to improvement in performance. Integrating multiple biometric traits recognition performance is improved and thereby reducing fraudulent access.The paper introduces an IBFS comprising of authentication systems that are Improved Fingerprint Recogni-tion System (IFPRS) and Improved Face Recognition System (IFRS) are introduced. Whale optimization algorithm is used with minutiae feature for IFPRS and Maximally Stable External Regions (MSER) for IFRS. To train the designed IBFS, Pattern net model is used as a classification algorithm. Pattern net works based on processed data set along with SVM to train the IBFS model to achieve better classification accuracy. It is observed that the proposed fusion system exhibited average true positive rate and accuracy of 99.8 percentage and 99.6 percentage, respectively.

Highlights

The unimodal biometric systems are prone to the inconsistencies scores and outliers [1]
This work aims to present a new biometric system that overcomes the problem of authenticity and employs fusion of faces and fingerprint traits [2].The paper organizes in following sections: Section 2 defines the existing work in fingerprint and face biometric traits in the form of related work
The results have shown that the proposed amalgamation have optimized better performance than the uni-biometric system [11]

Summary

Introduction

The unimodal biometric systems are prone to the inconsistencies scores and outliers [1]. Fusion biometric systems or multi model systems play a crucial role in providing accuracy, security, universality and cost-effectiveness. Various research papers has focused on the face and fingerprintbased fusion system, but classification accuracy has not been achieved so far. This work aims to present a new biometric system that overcomes the problem of authenticity and employs fusion of faces and fingerprint traits [2].The paper organizes in following sections: Section 2 defines the existing work in fingerprint and face biometric traits in the form of related work.

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