GUC100 Multisensor Fingerprint Database for In-House (Semipublic) Performance Test. (5th September 2010)

• Record Type: Journal Article
• Authors: Gafurov, Davrondzhon; Bours, Patrick; Yang, Bian; Busch, Christoph
• Other Names: Dorizzi Bernadette Academic Editor.
• Is Part Of: EURASIP journal on information security. Volume 2010(2010)
• Publication Date: 2010-09-05
• Subjects: Computer security -- Periodicals; Computer networks -- Security measures -- Periodicals; Data encryption (Computer science) -- Periodicals; Cryptography -- Periodicals; 005.8
• DOI: 10.1155/2010/391761
• Languages: English
• ISSNs: 1687-417X

Abstract

Abstract : For evaluation of biometric performance of biometric components and system, the availability of independent databases and desirably independent evaluators is important. Both databases of significant size and independent testing institutions provide the precondition for fair and unbiased benchmarking. In order to show generalization capabilities of the system under test, it is essential that algorithm developers do not have access to the testing database, and thus the risk of tuned algorithms is minimized. In this paper, we describe the GUC100 multiscanner fingerprint database that has been created for independent and in-house (semipublic) performance and interoperability testing of third party algorithms. The GUC100 was collected by using six different fingerprint scanners (TST, L-1, Cross Match, Precise Biometrics, Lumidigm, and Sagem). Over several months, fingerprint images of all 10 fingers from 100 subjects on all 6 scanners were acquired. In total, GUC100 contains almost 72.000 fingerprint images. The GUC100 database enables us to evaluate various performances and interoperability settings by taking into account different influencing factors such as fingerprint scanner and image quality. The GUC100 data set is freely available to other researchers and practitioners provided that they conduct their testing in the premises of the Gjøvik University College in Norway, or alternatively submit their algorithms (in compiled form) to run on GUC100 by researchers in Gjøvik. We applied one public and one commercial fingerprint verification algorithm on GUC100, and the reported results indicate that GUC100 is a challenging database.