Fuzzy logic decision fusion in a multimodal biometric system

This paper presents a multi-biometric verification system that combines speaker verification, fingerprint verification with face identification. Their respective equal error rates (EER) are 4.3%, 5.1% and the range of (5.1% to 11.5%) for matched conditions in facial image capture. Fusion of the three by majority voting gave a relative improvement of 48% over speaker verification (i.e. the best-performing biometric). Fusion by weighted average scores produced a further relative improvement of 52%. We propose the use of fuzzy logic decision fusion, in order to account for external conditions that affect verification performance. Examples include recording conditions of utterances for speaker verification, lighting and facial expressions in face identification and finger placement and pressure for fingerprint verification. The fuzzy logic framework incorporates some external factors relating to face and fingerprint verification and achieved an additional improvement of 19%.