Selective Small Reconstruction Error Based LDRC Multimodal Biometric Authentication

Savitha G.¹ , Vibha L.² , Venugopal K. R.³

1. Dept. Computer Science and Engineering, B.N.M. Institute of Technology, Bangalore, India.
2. Dept. Computer Science and Engineering, B.N.M. Institute of Technology, of University, Bangalore, India.
3. Dept. Computer Science and Engineering, Visvesvaraya College of Engineering, Bangalore, India.

Correspondence should be addressed to: savithaphd2016@gmail.com.

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.1 , pp.1-10, Feb-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i1.110

Online published on Feb 28, 2018

Copyright © Savitha G., Vibha L., Venugopal K. R. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Biometric authentication has attracted great interest due to its importance in numerous real-world applications. In this paper, the accuracy issue addressed through multimodal biometric combination. The proposed multimodal biometric combination scheme delivers face, finger print and signature as biometric characteristics, as an input for security purpose. The proposed methodology incorporates Wiener filter for preprocessing the acquired images and Discrete Wavelet Transform (DWT) was used for achieving feature subsets. Then, Linear Discriminant Regression Classification (LDRC) was designed with the combination of Selective Small Reconstruction Error (SSRE), which helps to select the appropriate classes. In experimental analysis, the proposed approach improves the authentication rate by means of False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER). The experimental outcome shows that the proposed methodology improved accuracy in biometric authentication rate up to 5-10% compared to the existing method: Linear Regression Classification (LRC).

Key-Words / Index Term :
Biometric Authentication; Discrete Wavelet Transform; Selective Small Reconstruction Error; Wiener Filter

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