Finger image quality based on singular point localization

Singular points are important global features of fingerprints and singular point localization is a crucial step in biometric recognition. Moreover the presence and position of the core point in a captured fingerprint sample can reflect whether the finger is placed properly on the sensor. Therefore, the displacement given by detected core points is investigated. We propose pattern-based filters to eliminate the false detection given by state of the art approaches. The experimental results show improvement using different databases. Based on the improved singular point localization algorithm, we explore and analyze the importance of singular points on biometric accuracy. The experiment is based on large scale databases and conducted by relating the measured quality of a fingerprint sample, given by the positions of core points, to the biometric performance. The experimental results show the positions of core points do have influence on the comparison algorithms, but are not as relevant as other benchmarked quality metrics.

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

[2]  Anil K. Jain,et al.  Biometric cryptosystems: issues and challenges , 2004, Proceedings of the IEEE.

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

[4]  Zohreh Mousavinasab,et al.  Biometric Systems , 2013 .

[5]  Ali N. Akansu,et al.  A class of fast Gaussian binomial filters for speech and image processing , 1991, IEEE Trans. Signal Process..

[6]  Andrew P. Witkin,et al.  Analyzing Oriented Patterns , 1985, IJCAI.

[7]  Tong Liu,et al.  Fingerprint Reference Point Detection Based on Local Axial Symmetry , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[8]  Liu Wei,et al.  Fingerprint Classification Using Singularities Detection , 2008 .

[9]  Haiyun Xu,et al.  Gabor filters as candidate quality measure for NFIQ 2.0 , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[10]  Dzulkifli Mohamad,et al.  A Review on Fingerprint Classification Techniques , 2009, 2009 International Conference on Computer Technology and Development.

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

[12]  Babu M. Mehtre,et al.  Fingerprint image analysis for automatic identification , 1993, Machine Vision and Applications.

[13]  Tony Lindeberg,et al.  Feature Detection with Automatic Scale Selection , 1998, International Journal of Computer Vision.

[14]  Bala Srinivasan,et al.  Fingerprint reference point detection based on local ridge orientation patterns of fingerprints , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

[15]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[16]  Steven W. Smith,et al.  The Scientist and Engineer's Guide to Digital Signal Processing , 1997 .

[17]  Jiankun Hu,et al.  A Gradient Based Weighted Averaging Method for Estimation of Fingerprint Orientation Fields , 2005, Digital Image Computing: Techniques and Applications (DICTA'05).

[18]  V. S. Srinivasan,et al.  Detection of singular points in fingerprint images , 1992, Pattern Recognit..

[19]  Xudong Jiang,et al.  Fingerprint image quality analysis , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[20]  Elham Tabassi,et al.  Performance of Biometric Quality Measures , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Charles L. Wilson,et al.  A novel approach to fingerprint image quality , 2005, IEEE International Conference on Image Processing 2005.

[22]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[23]  Anil K. Jain,et al.  A Multichannel Approach to Ngerprint Classiication , 1999 .

[24]  Xudong Jiang,et al.  Fingerprint quality and validity analysis , 2002, Proceedings. International Conference on Image Processing.

[25]  Anil K. Jain,et al.  A Multichannel Approach to Fingerprint Classification , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  C. I. Watson,et al.  NIST Special Database 10 , 1993 .

[27]  Hakil Kim,et al.  Pixel-level singular point detection from multi-scale Gaussian filtered orientation field , 2010, Pattern Recognit..

[28]  Alvin F. Martin,et al.  The DET curve in assessment of detection task performance , 1997, EUROSPEECH.

[29]  Ronald F. Boisvert,et al.  NIST Handbook of Mathematical Functions , 2010 .

[30]  Tong Liu,et al.  Fingerprint indexing based on singular point correlation , 2005, IEEE International Conference on Image Processing 2005.

[31]  J. Rodgers,et al.  Thirteen ways to look at the correlation coefficient , 1988 .

[32]  Raymond N. J. Veldhuis,et al.  Likelihood-ratio-based biometric verification , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

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

[34]  Anil K. Jain.  Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[35]  Axel Munk,et al.  Robust Orientation Field Estimation and Extrapolation Using Semilocal Line Sensors , 2009, IEEE Transactions on Information Forensics and Security.

[36]  M. Zweig,et al.  Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. , 1993, Clinical chemistry.

[37]  Yilong Yin,et al.  Singular points detection based on multi-resolution in fingerprint images , 2011, Neurocomputing.

[38]  Sabih H. Gerez,et al.  Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[39]  Christoph Busch,et al.  Semantic conformance testing for finger minutiae data , 2009, 2009 Proceedings of the 1st International Workshop on Security and Communication Networks.

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

[41]  Anil K. Jain,et al.  Encyclopedia of Biometrics , 2015, Springer US.

[42]  C. Spearman.  The proof and measurement of association between two things. , 2015, International journal of epidemiology.

[43]  Jiankun Hu,et al.  Enhanced gradient-based algorithm for the estimation of fingerprint orientation fields , 2007, Appl. Math. Comput..

[44]  Yoshihiko Hamamoto,et al.  A gabor filter-based method for recognizing handwritten numerals , 1998, Pattern Recognit..

[45]  Akio Tojo,et al.  Fingerprint pattern classification , 1984, Pattern Recognit..

[46]  Pedro R. Vizcaya,et al.  A nonlinear orientation model for global description of fingerprints , 1996, Pattern Recognit..

[47]  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 .

[48]  Sung-Bae Cho,et al.  Adaptive fingerprint image enhancement with fingerprint image quality analysis , 2006, Image Vis. Comput..

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

[50]  Alessandra Lumini,et al.  Fingerprint Classification by Directional Image Partitioning , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[51]  Sharath Pankanti,et al.  Fingerprint enhancement , 1996, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96.

[52]  J. Patel,et al.  Handbook of the normal distribution , 1983 .

[53]  David Zhang,et al.  A combination model for orientation field of fingerprints , 2004, Pattern Recognit..