Statistical analysis of fingerprint sensor interoperability performance

Authors:
Shimon K. Modi;Stephen J. Elliott;Hale Kim
Affiliations:
Biometric Standards Performance and Assurance Laboratory, Purdue University, West Lafayette, IN;Industrial Technology Department, Biometric Standards Performance and Assurance Laboratory, Purdue University, West Lafayette, IN;School of Information and Communication Engineering, INHA, Incheon, Korea
Venue:
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Year:
2009

Citing 3
Cited 0

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International Journal of Computer Applications in Technology

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Abstract

The proliferation of networked authentication systems has put focus on the issue of interoperability. Fingerprint sensors are based on a variety of different technologies that introduce inconsistent distortions and variations in the feature set of the captured image, which makes the goal of interoperability challenging. The motivation of this research was to examine the effect of fingerprint sensor interoperability on the performance of a minutiae based matcher. A statistical analysis framework for testing interoperability was formulated to test similarity of minutiae count, image quality and similarity of performance between native and interoperable datasets. False non-match rate (FNMR) was used as the performance metric in this research. Interoperability performance analysis was conducted on each sensor dataset and also by grouping datasets based on the acquisition technology and interaction type of the acquisition sensor. The lowest interoperable FNMR observed was 0.12%.