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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ReportDOI
Investigating Cognitive Rhythms as a New Modality for Continuous Authentication
TL;DR: The research under this project focused on defining and extracting cognitive rhythms from users' text production data, determining the availability and discriminability of cognitive rhythm features for continuous authentication, and investigating the impact of non-zero effort forgery attacks against continuous authentication.
Proceedings ArticleDOI
A rank minimization-based late fusion method for multi-label image annotation
TL;DR: This paper proposes a new method of late fusion for image annotation based on rank minimization that avoids normalization by transforming confidence score vectors into pairwise relationship matrices and obtains an optimal matrix.
Book ChapterDOI
A Novel Method for Multibiometric Fusion Based on FAR and FRR
TL;DR: A novel approach for score level fusion which is based on FAR and FRR is proposed and the experimental results show that the new fusion scheme is efficient for different Multibiometric systems.
Proceedings ArticleDOI
Bayesian score level fusion for facial recognition
Marco F. Huber,Andreas Merentitis,Roel Heremans,Maria Niessen,Christian Debes,Nikolaos Frangiadakis +5 more
TL;DR: A novel fusion algorithm operating on match score level is proposed that follows Bayesian inference and decision theory and facilitates the incorporation of temporal correlation between detections.
Patent
Automated identification of documents as not belonging to any language
TL;DR: In this paper, an impostor profile for a language is used to determine whether documents are in that language or no language, and then a most likely language for a test document is identified.
References
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Journal ArticleDOI
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