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DPD-DFF: a dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases

Peralta, Daniel; Triguero, Isaac; Garc�a, Salvador; Herrera, Francisco; Benitez, Jose M.

DPD-DFF: a dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases Thumbnail


Authors

Daniel Peralta

Salvador Garc�a

Francisco Herrera

Jose M. Benitez



Abstract

Nowadays, many companies and institutions need fast and reliable identification systems that are able to deal with very large databases. Fingerprints are among the most used biometric traits for identification. In the current literature there are fingerprint matching algorithms that are focused on efficiency, whilst others are based on accuracy. In this paper we propose a flexible dual phase identification method, called DPD-DFF, that combines two fingers and two matchers within a hybrid fusion scheme to obtain both fast and accurate results. Different alternatives are designed to find a trade-off between runtime and accuracy that can be further tuned with a single parameter. The experiments show that DPD-DFF obtains very competitive results in comparison with the state-of-the-art score fusion techniques, especially when dealing with large databases or impostor fingerprints.

Citation

Peralta, D., Triguero, I., García, S., Herrera, F., & Benitez, J. M. (2016). DPD-DFF: a dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases. Information Fusion, 32(Part A), https://doi.org/10.1016/j.inffus.2016.03.002

Journal Article Type Article
Acceptance Date Mar 13, 2016
Online Publication Date Mar 22, 2016
Publication Date Nov 1, 2016
Deposit Date Jun 8, 2016
Publicly Available Date Jun 8, 2016
Journal Information Fusion
Print ISSN 1566-2535
Electronic ISSN 1566-2535
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 32
Issue Part A
DOI https://doi.org/10.1016/j.inffus.2016.03.002
Keywords Real-time identification; Large databases; Minutiae matching; Fingerprint fusion; Decision fusion; Score fusion; Parallel computing; Biometrics
Public URL https://nottingham-repository.worktribe.com/output/974392
Publisher URL http://dx.doi.org/10.1016/j.inffus.2016.03.002

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