Online Fingerprint Template Improvement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Template Adaptation based Fingerprint Verification
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
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
Wolf attack probability: a new security measure in biometric authentication systems
ICB'07 Proceedings of the 2007 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
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Biometric system adaptation by self-update and graph-based techniques
Journal of Visual Languages and Computing
Analysis of unsupervised template update in biometric recognition systems
Pattern Recognition Letters
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Current methods for automatic template update are aimed at capturing large intra-class variations of input data and at the same time restricting the probability of impostor's introduction in client's galleries. These automatic methods avoid the costs of supervised update methods, which are due to repeated enrollment sessions and manual assignment of identity labels. Most of state-of-the-art template update approaches add input patterns to the claimed identity's gallery on the basis of their matching score with the existing templates, which must be above a very high "updating" threshold. However, regardless of the value of such updating threshold, update errors do exist and impact strongly on the effectiveness of update procedures. The introduction of impostors into the galleries may degrade the performance quickly. This effect has not been studied in the literature so far. Therefore, a first experimental investigation is the goal of this paper, with a case study on a face verification system.