Abstract
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.
Original language | English |
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Article number | 6974071 |
Pages (from-to) | 1165-1170 |
Number of pages | 6 |
Journal | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
Volume | 2014-January |
Issue number | January |
DOIs | |
Publication status | Published - 2014 |
Event | 2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States Duration: 5 Oct 2014 → 8 Oct 2014 |
Scopus Subject Areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction