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Large Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems

Published

Author(s)

Robert D. Snelick, U Uludag, Alan Mink, Michael D. Indovina, A Jain

Abstract

We examine the performance of multimodal biometric authentication systems using state-of-the-art Commercial Off-the-Shelf (COTS) fingerprint and face biometric systems on a population approaching 1,000 individuals. Majority of prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations of a few hundred users. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce new methods of normalization and fusion that further improve the accuracy.
Citation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume
27
Issue
3

Citation

Snelick, R. , Uludag, U. , Mink, A. , Indovina, M. and Jain, A. (2005), Large Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=150184 (Accessed April 22, 2024)
Created February 28, 2005, Updated October 12, 2021