Incorporating Image Quality in Multimodal Biometric Verification
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
On estimating performance indices for biometric identification
Pattern Recognition
Multi-normalization: a new method for improving biometric fusion
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
On some performance indices for biometric identification system
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Most biometric verification techniques make decisions based solely on a score that represents the similarity of the query template with the reference template of the claimed identity stored in the database. When multiple templates are available, a fusion scheme can be designed using the similarities with these templates. Combining several templates to construct a composite template and selecting a set of useful templates has also been reported in addition to usual multi-classifier fusion methods when multiple matchers are available. These commonly adopted techniques rarely make use of the large number of non-matching templates in the database or training set. In this paper, we highlight the usefulness of such a fusion scheme while focusing on the problem of fingerprint verification. For each enrolled template, we identify its cohorts (similar fingerprints) based on a selection criterion. The similarity scores of the query template with the reference template and its cohorts from the database are used to make the final verification decision using two approaches: a likelihood ratio based normalization scheme and a Support Vector Machine (SVM)-based classifier. We demonstrate the accuracy improvements using the proposed method with no a priori knowledge about the database or the matcher under consideration using a publicly available database and matcher. Using our cohort selection procedure and the trained SVM, we show that accuracy can be significantly improved at the expense of few extra matches.