ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Speaker verification using speaker- and test-dependent fast score normalization
Pattern Recognition Letters
The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Calculation of a composite DET curve
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Incorporating Model-Specific Score Distribution in Speaker Verification Systems
IEEE Transactions on Audio, Speech, and Language Processing
Target dependent score normalization techniques and their application to signature verification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Cohort-based score normalization as examplified by the T-norm (for Test normalization) has been the state-of-the-art approach to account for the variability of signal quality in testing. On the other hand, user-specific score normalization such as the Z-norm and the F-norm, designed to handle variability in performance across different reference models, has also been shown to be very effective. Exploiting the strenghth of both approaches, this paper proposes a novel score normalization called adaptive F-norm, which is client-impostor centric, i.e., utilizing both the genuine and impostor score information, as well as adaptive, i.e, adaptive to the test condition thanks to the use of a pool of cohort models. Experiments based on the BioSecure DS2 database which contains 6 fingers of 415 subjects, each acquired using a thermal and an optical device, show that the proposed adaptive F-norm is better or at least as good as the other alternatives, including those recently proposed in the literature.