Modelling FRR of Biometric Verification Systems Using the Template Co-update Algorithm

Authors:
Luca Didaci;Gian Luca Marcialis;Fabio Roli
Affiliations:
Dept. of Electrical and Electronic Eng., University of Cagliari, Italy;Dept. of Electrical and Electronic Eng., University of Cagliari, Italy;Dept. of Electrical and Electronic Eng., University of Cagliari, Italy
Venue:
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Year:
2009

Citing 10
Cited 2

On-Line Fingerprint Verification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Fingerprint Template Improvement

IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Fingerprint Recognition

Handbook of Fingerprint Recognition
Handbook of Face Recognition

Handbook of Face Recognition
Handbook of Multibiometrics (International Series on Biometrics)

Handbook of Multibiometrics (International Series on Biometrics)
Template Adaptation based Fingerprint Verification

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Eigenfaces for recognition

Journal of Cognitive Neuroscience
Template Co-update in Multimodal Biometric Systems

ICB '07 Proceedings of the international conference on Advances in Biometrics
A Theoretical and Experimental Analysis of Template Co-update in Biometric Verification Systems

SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Semi-supervised PCA-Based face recognition using self-training

SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition

Maximum Membership Scale Selection

MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Analysis of unsupervised template update in biometric recognition systems

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

The decrease of representativeness of available templates during time is due to the large intra-class variations characterizing biometrics (e.g. faces). This requires the design of algorithms able to make biometric verification systems adaptive to such variations. Among others, the template co-update algorithm, which uses the mutual help of two complementary biometric matchers, has shown promising experimental results. The present paper is aimed to describe a theoretical model able to explain the co-update behaviour. In particular, the focus is on the relationships between error rate and gallery size increase. Preliminary experimental results are shown to validate the proposed model.