FVC2000: Fingerprint Verification Competition

By Dario Maio, Davide Maltoni, Raffaele Cappelli, James L. Wayman, Anil K. Jain. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002

908 citations recorded by the source corpus.

Reliable and accurate fingerprint recognition is a challenging pattern recognition problem, requiring algorithms robust in many contexts. FVC2000 competition attempted to establish the first common benchmark, allowing companies and academic institutions to unambiguously compare performance and track improvements in their fingerprint recognition algorithms. Three databases were created using different state-of-the-art sensors and a fourth database was artificially generated; 11 algorithms were extensively tested on the four data sets. We believe that FVC2000 protocol, databases, and results will be useful to all practitioners in the field not only as a benchmark for improving methods, but also for enabling an unbiased evaluation of algorithms.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/3aba7b3c1664d22d87463ff8cfd5f133339a130a

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Citations in the corpus

Performance evaluation of fingerprint verification systems (2006, methodology): “Current scientific papers on fingerprint recognition now regularly report results using the publicly-available databases collected in our previous competitions [17], [18].”
FVC2002: Second Fingerprint Verification Competition (2002, methodology): “The First International Fingerprint Verification Competition (FVC2000) was organized by the authors in the year 2000 and the results were presented at 15' ICPR [I].”
Fingerprint recognition by combining global structure and local cues (2006, methodology): “Therefore, we tested our proposed algorithm on DB3 and DB4 using the experimental protocols proposed in [31].”
Biometric cryptosystems: issues and challenges (2004, methodology): “used in our experiments [29] is not as good as those reported in the literature more recently [30].”
Practical Biometric Authentication with Template Protection (2005, methodology): “i) The first fingerprint database we used is the second FVC2000 [ Mai00 ] database.”
3DPeS: 3D people dataset for surveillance and forensics (2011, background): “The new assessed version of the dataset contains hundreds of video sequences of 200 people taken from a multi-camera distributed surveillance system over several days, with di.erent light conditions; each person is detected multiple times and from di.erent points of view.”
A survey of biometric recognition methods (2004, methodology): “Fingerprint FVC2002 [3] Users mostly in the age group 20-39 0.”
An introduction to biometric recognition (2004, background): “A detailed discussion on these issues is available in [25] and [27].”
Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition (2010, neutral): “. Equal-Error-Rate (EER) [ 49 ]; . FMR1000 (the lowest FNMR for FMR � 0:1%) [34]; . average matching time, subdivided into:”
Comparing passwords, tokens, and biometrics for user authentication (2003, neutral): “–Aug 2000; fingerprint; 500 dpi, 256 364 size capacitive sensor (test “DB2”) 100 fingerprints [55].”
Fingerprint Matching Using an Orientation-Based Minutia Descriptor (2003, methodology): “For this experiment, we selected 40 pairs of fingerprint images from the database DB1 [19], and manually identified corresponding minutiae between the two images in each pair.”
ICDAR 2003 robust reading competitions (2003, methodology): “We aimed to broadly follow the principles and procedures used to run the Fingerprint Verification 2000 (and 2002) competitions [6].”
On the individuality fingerprints (2001, methodology): “The fingerprint correspondence probabilities (false acceptance rates) obtained on these databases are consistent with those obtained on similar databases by several other state-of-the-art automatic fingerprint verification systems reported in the FVC2000 Fingerprint Verification Competition [12].”