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.

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: 1872-6305
• 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
• Contract Date: Jun 8, 2016