Robust multimodal biometric verification system based on face and fingerprint
H. D. Supreetha Gowda, Govindaraju Hemantha Kumar, Mohammad Imran · 2017
In this paper, we have proposed a multimodal biometric verification system adopting the physiological traits-face and fingerprint. The system has been evaluated for robustness analysis imposing the Additive White Gaussian noise (AWGN) on clean data of the employed databases-AR facial database, PolyU High-resolution fingerprint database. The unimodal and multimodal (pre and post matching fusion strategies) verification system is investigated extracting the log-gabor features. Considering the performance measures such as GAR (Genuine Acceptance Rate) and FAR (False Acceptance Rate) at the benchmark threshold values - 0.01%, 0.1%, 1%. The accuracy of the system for clean and noisy data can be visualized by ROC (Receiver Operating Characteristics) curve, area under it expresses the performance of the implemented system.