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.

View at publisher

Abstract

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.

Impact and interest:

0 citations in Scopus
Search Google Scholar™
2 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 50593
Item Type: Journal Article
Refereed: Yes
DOI: 10.1007/978-3-642-23678-5_4
ISBN: 978-3-642-23678-5
ISSN: 1611-3349
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

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page