Document Type
Conference Paper
Department/Unit
Department of Computer Science
Title
A supervised correlation analysis for score-level calibration of cross-device fingerprint recognition
Language
English
Abstract
© 2014 IEEE. As the usage of fingerprint systems is rolled out on a large scale, scenarios have cross-device matching to allow information exchange and provide compatibility to the existing systems. A score-level calibration for device interoperability will require normalizing scores obtained from different devices so that they can be matched meaningfully and effectively. Conventional methods either assume a homogeneous distribution or model score distribution based on assumptions that may not be valid. In this paper, we circumvent the problem by leveraging correlations among the scores and propose a novel method for biometric score normalization. Our experiments show the promising results.
Publication Date
2014
Source Publication Title
Proceedings 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Start Page
1165
End Page
1170
Conference Location
San Diego, United States
Publisher
IEEE
DOI
10.1109/SMC.2014.6974071
Link to Publisher's Edition
http://dx.doi.org/10.1109/SMC.2014.6974071
ISBN (print)
9781479938407
Recommended Citation
Gu, Fangqing, Yi Wang, and Yiu-Ming Cheung. "A supervised correlation analysis for score-level calibration of cross-device fingerprint recognition." Proceedings 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2014): 1165-1170.