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 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
Journal of Cognitive Neuroscience
Template Co-update in Multimodal Biometric Systems
ICB '07 Proceedings of the international conference on Advances in Biometrics
Replacement Algorithms for Fingerprint Template Update
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Handbook of Fingerprint Recognition
Handbook of Fingerprint 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
Modelling FRR of Biometric Verification Systems Using the Template Co-update Algorithm
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Template Update Methods in Adaptive Biometric Systems: A Critical Review
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Analysis of unsupervised template update in biometric recognition systems
Pattern Recognition Letters
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Template update in biometric recognition system is aimed to improve the representativeness of available templates in order to make them adaptive to the large intra-class variations characterizing biometrics (e.g. fingerprints and faces). Among others, semi-supervised approaches to template update have been recently proposed. Since the lack of representativeness is due to the impossibility of sampling all possible variations of a given client biometric, these approaches exploit samples submitted during the recognition phase by adding the "highly genuine" ones to the related client gallery. In particular, the template co-update algorithm, which uses the mutual help of two complementary biometric matchers, has shown promising experimental results. However, no theoretical model has been proposed to explain the behaviour of the co-update algorithm and support the experimental results. This is the goal of this paper. Experimental results show the correctness of the proposed theoretical model.