Multimodal Biometric Authentication Methods : A COTS Approach

We examine the performance of multimodal biometric authentication systems using state-of-the-art Commercial Off-the-Shelf (COTS) fingerprint and face biometrics on a population approaching 1000 individuals. Prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations approximately 10% of this size. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using already highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce novel methods of fusion and normalization that improve accuracy still further through population analysis.

[1]  Douglas A. Reynolds,et al.  SHEEP, GOATS, LAMBS and WOLVES A Statistical Analysis of Speaker Performance in the NIST 1998 Speaker Recognition Evaluation , 1998 .

[2]  Sharath Pankanti,et al.  Evaluation techniques for biometrics-based authentication systems (FRR) , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[3]  Arun Ross,et al.  Information fusion in biometrics , 2003, Pattern Recognit. Lett..

[4]  Arun Ross,et al.  Learning user-specific parameters in a multibiometric system , 2002, Proceedings. International Conference on Image Processing.

[5]  SUMMARY OF NIST STANDARDS FOR BIOMETRIC ACCURACY, TAMPER RESISTANCE, AND INTEROPERABILITY , 2002 .

[6]  Alan Mink,et al.  Multimodal biometrics: issues in design and testing , 2003, ICMI '03.

[7]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.