Selective Small Reconstruction Error Based LDRC Multimodal Biometric Authentication
Keywords:
Biometric Authentication, Discrete Wavelet Transform, Selective Small Reconstruction Error, Wiener FilterAbstract
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).
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