DPD-DFF: A Dual Phase Distributed Scheme with Double Fingerprint Fusion for Fast and Accurate Identification in Large Databases Peralta, Daniel Triguero, Isaac García López, Salvador Herrera Triguero, Francisco Benítez Sánchez, José Manuel Real-time identification Large databases Minutiae matching Fingerprint fusion Decision fusion Score fusion Parallel Computing Biometrics This work was supported by the research projects TIN2014-57251-P, TIN2013-47210-P and P12-TIC-2958. D. Peralta holds an FPU scholarship from the Spanish Ministry of Education and Science (FPU12/04902). I. Triguero holds a BOF postdoctoral fellowship from the Ghent University. 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. 2020-12-23T11:21:14Z 2020-12-23T11:21:14Z 2016-06-08 info:eu-repo/semantics/article Published version: 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, 40-51. [https://doi.org/10.1016/j.inffus.2016.03.002] http://hdl.handle.net/10481/65130 10.1016/j.inffus.2016.03.002 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess Atribución-NoComercial-SinDerivadas 3.0 España Elsevier