Sequential Fusion Using Correlated Decisions for Controlled Verification Errors
Nallagatla, Vishnu Priya & Chandran, Vinod (2011) Sequential Fusion Using Correlated Decisions for Controlled Verification Errors. Lecture Notes in Computer Science: Computer Analysis of Images and Patterns, 6855, pp. 49-56.
Fusion techniques have received considerable attention for achieving lower error rates with biometrics. A fused classifier architecture based on sequential integration of multi-instance and multi-sample fusion schemes allows controlled trade-off between false alarms and false rejects. Expressions for each type of error for the fused system have previously been derived for the case of statistically independent classifier decisions. It is shown in this paper that the performance of this architecture can be improved by modelling the correlation between classifier decisions. Correlation modelling also enables better tuning of fusion model parameters, ‘N’, the number of classifiers and ‘M’, the number of attempts/samples, and facilitates the determination of error bounds for false rejects and false accepts for each specific user. Error trade-off performance of the architecture is evaluated using HMM based speaker verification on utterances of individual digits. Results show that performance is improved for the case of favourable correlated decisions. The architecture investigated here is directly applicable to speaker verification from spoken digit strings such as credit card numbers in telephone or voice over internet protocol based applications. It is also applicable to other biometric modalities such as finger prints and handwriting samples.
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|Item Type:||Journal Article|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2011 Springer|
|Deposited On:||17 Jul 2012 23:51|
|Last Modified:||24 Aug 2012 04:59|
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