GUC100 Multisensor Fingerprint Database for In-House (Semipublic) Performance Test

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.

[1]  C. Busch,et al.  Investigating performance and impacts on fingerprint recognition systems , 2005, Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop.

[2]  Anil K. Jain,et al.  FVC2000: Fingerprint Verification Competition , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Julian Fiérrez,et al.  A Comparative Study of Fingerprint Image-Quality Estimation Methods , 2007, IEEE Transactions on Information Forensics and Security.

[4]  Hakil Kim,et al.  Resolution and Distortion Compensation based on Sensor Evaluation for Interoperable Fingerprint Recognition , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[5]  Raymond N. J. Veldhuis,et al.  Sensor Interoperability and Fusion in Fingerprint Verification: A Case Study using Minutiae-and Ridge-Based Matchers , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[6]  Arun Ross,et al.  Biometric Sensor Interoperability: A Case Study in Fingerprints , 2004, ECCV Workshop BioAW.

[7]  Christoph Busch,et al.  Independent performance evaluation of fingerprint verification at the minutiae and pseudonymous identifier levels , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[8]  Arun Ross,et al.  A Thin-Plate Spline Calibration Model For Fingerprint Sensor Interoperability , 2008, IEEE Transactions on Knowledge and Data Engineering.

[9]  Julian Fiérrez,et al.  Biosec baseline corpus: A multimodal biometric database , 2007, Pattern Recognit..

[10]  Anil K. Jain,et al.  FVC2002: Second Fingerprint Verification Competition , 2002, Object recognition supported by user interaction for service robots.

[11]  Richard Guest,et al.  Information technology -- 29107-7 Conformance testing methodology for biometric data interchange formats defined in ISO/IEC 19794 -- Part 7: Signature/sign time series data , 2011 .

[12]  Gérard Chollet,et al.  BIOMET: A Multimodal Person Authentication Database Including Face, Voice, Fingerprint, Hand and Signature Modalities , 2003, AVBPA.

[13]  Michael D. Garris,et al.  NIST Fingerprint Evaluations and Developments , 2006, Proceedings of the IEEE.

[14]  Anil K. Jain,et al.  Biometric Template Security , 2008, EURASIP J. Adv. Signal Process..

[15]  Juan J. Igarza,et al.  MCYT baseline corpus: a bimodal biometric database , 2003 .

[16]  Gian Luca Marcialis,et al.  Fingerprint verification by fusion of optical and capacitive sensors , 2004, Pattern Recognit. Lett..

[17]  Christoph Busch,et al.  GUC100 Multi-scanner Fingerprint Database for In-House (Semi-public) Performance and Interoperability Evaluation , 2010, 2010 International Conference on Computational Science and Its Applications.

[18]  Craig I. Watson,et al.  MINEX II Performance of Fingerprint Match-on-Card Algorithms - Phase II Report | NIST , 2008 .

[19]  Anil K. Jain,et al.  Performance evaluation of fingerprint verification systems , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Patrick J. Grother,et al.  Performance of Fingerprint Match-on-Card Algorithms Phase II / III Report NIST Interagency Report 7477 (Revision I) , 2009 .

[21]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.