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

Abstract

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.

Context-aware fusion: A case study on fusion of gait and face for human identification in video

“…In quality-based fusion, a quality assessment algorithm is necessary to calculate a quality score. The assessment usually focuses on the biometric samples themselves, using quality measures directly calculated from the data, such as the signal-to-noise-ratio [14,11] and the high frequency components of Discrete Cosine Transformation [17]. However, at least at present, a single quality assessment algorithm dealing with all influential context factors is still unrealistic.…”

“…While adaptive information fusion has recently attracted much attention in several areas, little work has been done for context-aware multi-biometric fusion. Some recent work on quality-based multimodal biometrics [11][12][13][14][15][16][17][18] can be viewed as the first few attempts toward context-aware multi-biometric fusion since the differences in data quality are usually caused by external context factors, such as sensor quality, illumination condition, background noise, etc. In quality-based fusion, a quality assessment algorithm is necessary to calculate a quality score.…”

“…(10) regard all frame images in the training set while those in Eq (14). regard the m subsets in a video clip.…”

Fuzzy Logic Weight Estimation in Biometric-Enabled Co-authentication Systems

“…Regarding biometric-based co-authentication [3], [8], the use of "Fuzzy logic control system" as a method to estimate weight of biometric factors has been presented in many papers, such as [7] and [2]. In detail, the two systems proposed in [7] and [2] include membership functions and fuzzy logic rule sets for only three biometric traits (face, voice and fingerprint). In this paper, we present one construction that offers multi-feature verification system involving biometrics (face, voice) and non-biometric feature (password) to make the authentication system adaptive to mobile devices.…”