Article

Multimodal biometrics: issues in design and testing

Authors:

Robert Snelick,

Mike Indovina,

James Yen,

Alan MinkAuthors Info & Claims

ICMI '03: Proceedings of the 5th international conference on Multimodal interfaces

Pages 68 - 72

https://doi.org/10.1145/958432.958447

Published: 05 November 2003 Publication History

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Abstract

Experimental studies show that multimodal biometric systems for small-scale populations perform better than single-mode biometric systems. We examine if such techniques scale to larger populations, introduce a methodology to test the performance of such systems, and assess the feasibility of using commercial off-the-shelf (COTS) products to construct deployable multimodal biometric systems. A key aspect of our approach is to leverage confidence level scores from preexisting single-mode data. An example presents a multimodal biometrics system analysis that explores various normalization and fusion techniques for face and fingerprint classifiers. This multimodal analysis uses a population of about 1000 subjects, a number ten-times larger than seen in any previously reported study. Experimental results combining face and fingerprint biometric classifiers reveal significant performance improvement over single-mode biometric systems.

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Schuiki JLinortner MWimmer GUhl A(2023)Extensive Threat Analysis of Vein Attack Databases and Attack Detection by Fusion of Comparison ScoresHandbook of Biometric Anti-Spoofing10.1007/978-981-19-5288-3_17(467-487)Online publication date: 24-Feb-2023
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Schuiki JLinortner MWimmer GUhl A(2022)Attack Detection for Finger and Palm Vein Biometrics by Fusion of Multiple Recognition AlgorithmsIEEE Transactions on Biometrics, Behavior, and Identity Science10.1109/TBIOM.2022.32128364:4(544-555)Online publication date: Oct-2022
https://doi.org/10.1109/TBIOM.2022.3212836
S P RThomas T(2022)Cancelable biometric scheme based on dynamic salting of random patchesMultimedia Tools and Applications10.1007/s11042-022-13764-582:10(14337-14366)Online publication date: 15-Sep-2022
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Index Terms

Multimodal biometrics: issues in design and testing
1. General and reference
  1. Cross-computing tools and techniques

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Information

Published In

ICMI '03: Proceedings of the 5th international conference on Multimodal interfaces

November 2003

318 pages

ISBN:1581136218

DOI:10.1145/958432

Conference Chair:
Sharon Oviatt
Oregon Health & Science University
,
Program Chairs:
Trevor Darrell
Massachusetts Institute of Technology
,
Mark Maybury
MITRE
,
Wolfgang Wahlster
DFKI, Germany

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 05 November 2003

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ICMI-PUI03: International Conference on Multimodal User Interfaces

November 5 - 7, 2003

British Columbia, Vancouver, Canada

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ICMI '03 Paper Acceptance Rate 45 of 130 submissions, 35%;

Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Schuiki JLinortner MWimmer GUhl A(2023)Extensive Threat Analysis of Vein Attack Databases and Attack Detection by Fusion of Comparison ScoresHandbook of Biometric Anti-Spoofing10.1007/978-981-19-5288-3_17(467-487)Online publication date: 24-Feb-2023
https://doi.org/10.1007/978-981-19-5288-3_17
Schuiki JLinortner MWimmer GUhl A(2022)Attack Detection for Finger and Palm Vein Biometrics by Fusion of Multiple Recognition AlgorithmsIEEE Transactions on Biometrics, Behavior, and Identity Science10.1109/TBIOM.2022.32128364:4(544-555)Online publication date: Oct-2022
https://doi.org/10.1109/TBIOM.2022.3212836
S P RThomas T(2022)Cancelable biometric scheme based on dynamic salting of random patchesMultimedia Tools and Applications10.1007/s11042-022-13764-582:10(14337-14366)Online publication date: 15-Sep-2022
https://doi.org/10.1007/s11042-022-13764-5
Li JZhang BZhang DLi JZhang BZhang D(2022)IntroductionInformation Fusion10.1007/978-981-16-8976-5_1(1-11)Online publication date: 14-Feb-2022
https://doi.org/10.1007/978-981-16-8976-5_1
Soviany SSoviany C(2022)Data Fusion in Multimodal BiometryBreakthroughs in Digital Biometrics and Forensics10.1007/978-3-031-10706-1_3(49-88)Online publication date: 15-Oct-2022
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Schuiki JWimmer GUhl A(2021)Vulnerability Assessment and Presentation Attack Detection Using a Set of Distinct Finger Vein Recognition Algorithms2021 IEEE International Joint Conference on Biometrics (IJCB)10.1109/IJCB52358.2021.9484351(1-7)Online publication date: 4-Aug-2021
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Sujatha ESathiya Jeba Sundar JDeivendran PIndumathi G(2021)Multimodal Biometric Algorithm Using IRIS, Finger Vein, Finger Print with Hybrid GA, PSO for AuthenticationData Analytics and Management10.1007/978-981-15-8335-3_22(267-283)Online publication date: 5-Jan-2021
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Adaptive feature set updating algorithm for multimodal biometrics

Multimodal Biometrics -- Sources, Architecture and Fusion Techniques: An Overview

Fusion of face and iris features for multimodal biometrics

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