Adaptive Weight Estimation in Multi-Biometric Verification using Fuzzy Logic Decision Fusion

This paper describes a multi-biometric verification system that is fully adaptive to variability in data acquisition using fuzzy logic decision fusion. The system uses fuzzy logic to dynamically alter the weight of three biometrics (face, fingerprint and speech), taking into account the variations during data acquisition (e.g. lighting, noise and user-device interactions). A specific decision boundary can be determined by this dynamic weight assignment to make the authentication decisions. An overall EER improvement of 42.1% relative to weighted average fusion has been achieved.