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
More filters
Book ChapterDOI
Multimodal Biometric Authentication Based on Score Normalization Technique
TL;DR: A method for the management of access control to ensure the desired level of security using the adaptive combination of multimodal matching scores using fingerprint, palmprint and voice is proposed.
Journal ArticleDOI
Potential advantages and limitations of using information fusion in media forensics—a discussion on the example of detecting face morphing attacks
TL;DR: In this article, the authors explain the reasons for reluctance to accept such a potentially very beneficial technique and illustrate the practical issues arising when applying fusion, i.e., a potentially negative impact on the classification accuracy, if wrongly used or parameterized, as well as the increased complexity and the inherently higher costs for plausibility validation, of fusion is in conflict with the fundamental requirements for forensics.
Proceedings ArticleDOI
Weighted I-Vector Based Text-Independent Speaker Verification System
TL;DR: The test results indicate that the use of proposed weighting the model and test vectors reduces the error rate of the speaker verification system significantly.
Proceedings ArticleDOI
A Robust Shadow Removal Technique Applying For Person Localization in a Surveillance Environment
TL;DR: This work contributes an effective pre-processing step in order to deploy vision-based localization services in surveillance environments by taking into account a density-based score fusion scheme based on a learning-based approach.
Proceedings ArticleDOI
Experimental investigation of OC-SVM for multibiometric score fusion
TL;DR: The obtained results show the effectiveness of the OC-SVM compared to the standard two-class SVM classifier as well as to other score fusion schemes.
References
More filters
BookDOI
Density estimation for statistics and data analysis
TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Book
Testing statistical hypotheses
TL;DR: The general decision problem, the Probability Background, Uniformly Most Powerful Tests, Unbiasedness, Theory and First Applications, and UNbiasedness: Applications to Normal Distributions, Invariance, Linear Hypotheses as discussed by the authors.
Journal ArticleDOI
On combining classifiers
TL;DR: A common theoretical framework for combining classifiers which use distinct pattern representations is developed and it is shown that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision.
Journal ArticleDOI
Unsupervised learning of finite mixture models
TL;DR: The novelty of the approach is that it does not use a model selection criterion to choose one among a set of preestimated candidate models; instead, it seamlessly integrate estimation and model selection in a single algorithm.
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.