Journal ArticleDOI
Likelihood Ratio-Based Biometric Score Fusion
TLDR
Experiments on three multibiometric databases indicate that the proposed fusion framework achieves consistently high performance compared to commonly used score fusion techniques based on score transformation and classification.Abstract:
Multibiometric systems fuse information from different sources to compensate for the limitations in performance of individual matchers. We propose a framework for the optimal combination of match scores that is based on the likelihood ratio test. The distributions of genuine and impostor match scores are modeled as finite Gaussian mixture model. The proposed fusion approach is general in its ability to handle 1) discrete values in biometric match score distributions, 2) arbitrary scales and distributions of match scores, 3) correlation between the scores of multiple matchers, and 4) sample quality of multiple biometric sources. Experiments on three multibiometric databases indicate that the proposed fusion framework achieves consistently high performance compared to commonly used score fusion techniques based on score transformation and classification.read more
Citations
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Journal ArticleDOI
Fusion of biometric systems using Boolean combination: an application to iris-based authentication
TL;DR: Experiments performed with four different commercial systems using anonymised data collected by the Canada Border Services Agency indicate that IBC fusion with interpolation can signicantly outperform related BC techniques and individual systems.
Journal ArticleDOI
Multimodal biometric score fusion using Gaussian mixture model and Monte Carlo method
TL;DR: A framework for optimal fusion of match scores based on Gaussian Mixture Model (GMM) and Monte Carlo sampling based hypothesis testing and the proposed fusion scheme achieves higher performance as compared with other contemporary state of art fusion techniques.
Book ChapterDOI
Machine Learning for Biometrics
TL;DR: This chapter presents a survey of machine learning methods used for biometrics applications, and focuses on three areas of interest: ofine methods for biometric template construction and recognition, information fusion methods for integrating multipleBiometrics to obtain robust results, and methods for dealing with temporal information.
Proceedings ArticleDOI
Interoperability between Fingerprint Biometric Systems: An Empirical Study
TL;DR: This paper presents a comprehensive analysis of dependability and interoperability attributes of fingerprint authentication and makes empirically-supported recommendations on their deployment strategies.
Book ChapterDOI
Security Analysis of Multimodal Biometric Systems against Spoof Attacks
Zahid Akhtar,Sandeep Kale +1 more
TL;DR: Investigation of behavior of fixed and trained score fusion rules, using real spoof attack samples, finds that trained rules are not only more flexible and accurate but more robust, also, against spoof attacks as compare to fixed rules.
References
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Journal ArticleDOI
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Journal ArticleDOI
Score normalization in multimodal biometric systems
TL;DR: Study of the performance of different normalization techniques and fusion rules in the context of a multimodal biometric system based on the face, fingerprint and hand-geometry traits of a user found that the application of min-max, z-score, and tanh normalization schemes followed by a simple sum of scores fusion method results in better recognition performance compared to other methods.