FVC2000: fingerprint verification competition

Maio, Dario; Maltoni, Davide; Cappelli, Raffaele; Wayman, James L.; Jain, Anil K.

doi:10.1109/34.990140

Cited by 582 publications

(303 citation statements)

References 14 publications

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“…These tests, which ÿrst took place in August 1994, make use of the FERET database (whose collection began in 1993 and has been growing ever since) a ÿxed testing procedure, and have become a de facto standard for comparison between di erent technologies for face recognition from still images [52]. Other relevant competitions include the National Institute of Standards and Technology (NIST) speaker recognition evaluations, or the ÿngerprint veriÿca-tion competition (FVC) [45].…”

Section: A General Bis Modelmentioning

confidence: 99%

Biometric identification systems

et al. 2003

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In this paper, we provide an overview of the fundamentals of biometric identiÿcation, together with a description of the main biometric technologies currently in use, all of them within a common reference framework. A comparison on di erent qualitative parameters of these technologies is also given, so that the reader may have a clear perspective of advantages and disadvantages of each. A section on multibiometrics describes the state of the art in making these systems work coordinately. Fusion at di erent conceptual levels is described. Finally, a section on commercial issues provides the reader a perspective of the main companies currently involved in this ÿeld. ?

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Section: A General Bis Modelmentioning

confidence: 99%

Biometric identification systems

et al. 2003

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“…"FVC 2000 Database1_a" [17] was used to evaluate the NIST software in this thesis. This Database consists of 100 users fingers with 8 different samples from each finger.…”

Section: Resultsmentioning

confidence: 99%

Implementation and evaluation of NIST Biometric Image Software for fingerprint recognition

Maddala

Tangellapally

Bartunek

et al. 2011

ISSNIP Biosignals and Biorobotics Conference 2011

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Fingerprints are rich in details which are in the form of discontinuities in ridges known as minutiae and are unique for each person. The main desire of this thesis is to implement and evaluate National Institute of Science and Technology (NIST) Biometric Image Software (NBIS) for fingerprint recognition using C language MEX-files. NBSI source code is written in ANSI C programming language. A system developed in Matlab environment using C language MEX-files is used for implemented and evaluated the NIST source code. Minutiae extraction and minutiae matching are performed by using a function developed with NBIS. The extracted minutiae are passed through the function with NBIS that match two minutiae patterns and produce a match score. Finally the performance of the system is evaluated on various fingerprint databases and results are presented in Receiver Operating characteristics (ROC) graphs.

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“…The description of FVC2000 DB3 [31] states that one third of the 19 volunteers were under 18 years of age. These prints could be easily enlarged to the predicted adult print size at 500 DPI using the scaling factor attained in [32], if additional information were available (the age and whether the fingerprints was acquired from a male or female person).…”

Section: D-minutiae Histogramsmentioning

confidence: 99%

“…Tests are conducted on the publicly avaivable fingerprint competitions of FVC2000, FVC2002 and FVC2004 [31,40,41]. Each competition consists of four databases (DB1-DB4): for the first three databases, fingerprints Figure 5: Global mean and variance of individual interridge distances per image for all images of FVC2000, FVC2002 and FVC2004 estimated by curved regions [35].…”

Section: The Test Of Realness: Training and Test Protocolmentioning

confidence: 99%

Separating the real from the synthetic: minutiae histograms as fingerprints of fingerprints

Gottschlich

Huckemann

2014

IET biom.

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In this study 1 we show that by the current state-of-the-art synthetically generated fingerprints can easily be discriminated from real fingerprints. We propose a non-parametric distribution based method using second order extended minutiae histograms (MHs) which can distinguish between real and synthetic prints with very high accuracy. MHs provide a fixed-length feature vector for a fingerprint which are invariant under rotation and translation. This 'test of realness' can be applied to synthetic fingerprints produced by any method. In this work, tests are conducted on the 12 publicly available databases of FVC2000, FVC2002 and FVC2004 which are well established benchmarks for evaluating the performance of fingerprint recognition algorithms; 3 of these 12 databases consist of artificial fingerprints generated by the SFinGe software. Additionally, we evaluate the discriminative performance on a database of synthetic fingerprints generated by the software of Bicz versus real fingerprint images. We conclude with suggestions for the improvement of synthetic fingerprint generation.

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FVC2000: fingerprint verification competition

Cited by 582 publications

References 14 publications

Biometric identification systems

Biometric identification systems

Implementation and evaluation of NIST Biometric Image Software for fingerprint recognition

Separating the real from the synthetic: minutiae histograms as fingerprints of fingerprints

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