Benchmarking Fingerprint Minutiae Extractors

The performance of a fingerprint recognition system hinges on the errors introduced in each of its modules: image acquisition, preprocessing, feature extraction, and matching. One of the most critical and fundamental steps in fingerprint recognition is robust and accurate minutiae extraction. Hence we conduct a repeatable and controlled evaluation of one open-source and three commercial-off-the-shelf (COTS) minutiae extractors in terms of their performance in minutiae detection and localization. We also evaluate their robustness against controlled levels of image degradations introduced in the fingerprint images. Experiments were conducted on (i) a total of 3,458 fingerprint images from five public-domain databases, and (ii) 40,000 synthetically generated fingerprint images. The contributions of this study include: (i) a benchmark for minutiae extractors and minutiae interoperability, and (ii) robustness of minutiae extractors against image degradations.

[1]  Hakil Kim,et al.  A Study on Performance Evaluation of Fingerprint Sensors , 2003, AVBPA.

[2]  Bernadette Dorizzi,et al.  Fingerprint and On-Line Signature Verification Competitions at ICB 2009 , 2009, ICB.

[3]  Craig I. Watson,et al.  Fingerprint Vendor Technology Evaluation 2003: Summary of Results and Analysis Report , 2004 .

[4]  Gian Luca Marcialis,et al.  LivDet 2013 Fingerprint Liveness Detection Competition 2013 , 2013, 2013 International Conference on Biometrics (ICB).

[5]  Anil K. Jain,et al.  Fingerprint Matching , 2010, Computer.

[6]  Dario Maio,et al.  Improving Fingerprint Orientation Extraction , 2011, IEEE Transactions on Information Forensics and Security.

[7]  Craig I. Watson,et al.  Fingerprint Vendor Technology Evaluation , 2014 .

[8]  Davide Maltoni,et al.  On the Operational Quality of Fingerprint Scanners , 2008, IEEE Transactions on Information Forensics and Security.

[9]  Anil K. Jain,et al.  FVC2004: Third Fingerprint Verification Competition , 2004, ICBA.

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

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

[12]  Christophe Charrier,et al.  The Influence of Fingerprint Image Degradations on the Performance of Biometric System and Quality Assessment , 2016, 2016 International Conference of the Biometrics Special Interest Group (BIOSIG).

[13]  Anil K. Jain,et al.  Adaptive flow orientation-based feature extraction in fingerprint images , 1995, Pattern Recognit..

[14]  Anil K. Jain,et al.  Design and Fabrication of 3D Fingerprint Targets , 2016, IEEE Transactions on Information Forensics and Security.

[15]  Julian Fierrez,et al.  Dealing with sensor interoperability in multi-biometrics: the UPM experience at the Biosecure Multimodal Evaluation 2007 , 2008, SPIE Defense + Commercial Sensing.

[16]  Anil K. Jain,et al.  Fingerprint Quality Indices for Predicting Authentication Performance , 2005, AVBPA.

[17]  Umut Uludag,et al.  Standard Fingerprint Databases: Manual Minutiae Labeling and Matcher Performance Analyses , 2013, ArXiv.