Biometric System and Data Analysis: Design, Evaluation, and Data Mining

Biometric systems are being used in more places and on a larger scale than ever before. As these systems mature, it is vital to ensure the practitioners responsible for development and deployment, have a strong understanding of the fundamentals of tuning biometric systems. The focus of biometric research over the past four decades has typically been on the bottom line: driving down system-wide error rates. In doing so, powerful recognition algorithms have been developed for a number of biometric modalities. These algorithms operate exceedingly well under test conditions. Books on biometrics tend to focus on biometric systems and their components, and differentiate between the various biometric modalities. Biometric System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. This professional book naturally leads to topics including data mining and prediction, which have been widely applied to other fields but not rigorously to biometrics, to be examined in detail. Biometric System and Data Analysis: Design, Evaluation, and Data Mining places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however are always accompanied by intuitive explanations that can be used to convey the essence of the statistical concepts to a general audience. This last point is an important one for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public. Biometric System and Data Analysis: Design, Evaluation, and Data Mining is designed for a professional audience composed of practitioners and researchers in industry. This book is also suitable as a reference for advanced-level students in computer science and engineering.

[1]  Michael E. Schuckers Estimation and sample size calculations for correlated binary error rates of biometric identification devices , 2003 .

[2]  Krzysztof Kryszczuk,et al.  Addressing the Vulnerabilities of Likelihood-Ratio-Based Face Verification , 2005, AVBPA.

[3]  Anil K. Jain,et al.  Validating a Biometric Authentication System: Sample Size Requirements , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Kuo-Chin Fan,et al.  The use of thermal images of palm-dorsa vein-patterns for biometric verification , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[5]  Shigeo Abe DrEng Pattern Classification , 2001, Springer London.

[6]  Adam Czajka Making iris recognition more reliable and spoof resistant , 2007 .

[7]  Neil Yager,et al.  Worms, Chameleons, Phantoms and Doves: New Additions to the Biometric Menagerie , 2007, 2007 IEEE Workshop on Automatic Identification Advanced Technologies.

[8]  J. Wayman,et al.  Biometric Evaluation Methodology Common Criteria Common Methodology for Information Technology Security Evaluation Biometric Evaluation Methodology Supplement [ BEM ] , 2002 .

[9]  B. Jovanovic,et al.  A Look at the Rule of Three , 1997 .

[10]  Thomas David Heseltine,et al.  Face recognition : two-dimensional and three-dimensional techniques , 2005 .

[11]  L Sirovich,et al.  Low-dimensional procedure for the characterization of human faces. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[12]  Satoshi Hoshino,et al.  Impact of artificial "gummy" fingers on fingerprint systems , 2002, IS&T/SPIE Electronic Imaging.

[13]  Aaron F. Bobick,et al.  Predicting Large Population Data Cumulative Match Characteristic Performance from Small Population Data , 2003, AVBPA.

[14]  Jr. J.P. Campbell,et al.  Speaker recognition: a tutorial , 1997, Proc. IEEE.

[15]  John D. Woodward,et al.  Biometrics: privacy's foe or privacy's friend? , 1997, Proc. IEEE.

[16]  Douglas A. Reynolds,et al.  The NIST speaker recognition evaluation - Overview, methodology, systems, results, perspective , 2000, Speech Commun..

[17]  N. Schenker,et al.  Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance? , 2003, Journal of insect science.

[18]  M. Drahansky,et al.  Liveness Detection for Biometric Systems Based on Papillary Lines , 2008, 2008 International Conference on Information Security and Assurance (isa 2008).

[19]  Alice J. O'Toole,et al.  Face Recognition Algorithms Surpass Humans Matching Faces Over Changes in Illumination , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[21]  J.P. Hube,et al.  Using Biometric Verification to Estimate Identification Performance , 2006, 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference.

[22]  Alice J. O'Toole,et al.  FRVT 2006 and ICE 2006 large-scale results , 2007 .

[23]  Simon A. Cole,et al.  History of Fingerprint Pattern Recognition , 2004 .

[24]  A. Ross,et al.  Multispectral Iris Analysis : A Preliminary Study , 2006 .

[25]  Dario Maio,et al.  Synthetic fingerprint-image generation , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[26]  Vinod Chandran,et al.  3D Face Recognition using Log-Gabor Templates , 2006, BMVC.

[27]  A. Agresti,et al.  Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions , 1998 .

[28]  Craig I. Watson,et al.  The myth of goats :: how many people have fingerprints that are hard to match? , 2005 .

[29]  Harry Wechsler,et al.  The FERET database and evaluation procedure for face-recognition algorithms , 1998, Image Vis. Comput..

[30]  James L. Wayman,et al.  Multifinger Penetration Rate and ROC Variability for Automatic Fingerprint Identification Systems , 2004 .

[31]  Robert S. Boyer,et al.  Automated Reasoning: Essays in Honor of Woody Bledsoe , 1991, Automated Reasoning.

[32]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[33]  J. L. Wayman,et al.  Best practices in testing and reporting performance of biometric devices. , 2002 .

[34]  Neil Yager,et al.  The Biometric Menagerie , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Douglas A. Reynolds,et al.  SHEEP, GOATS, LAMBS and WOLVES A Statistical Analysis of Speaker Performance in the NIST 1998 Speaker Recognition Evaluation , 1998 .

[36]  M. Faundez-Zanuy,et al.  On the vulnerability of biometric security systems , 2004, IEEE Aerospace and Electronic Systems Magazine.

[37]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[38]  Tom Fawcett,et al.  ROC Graphs: Notes and Practical Considerations for Researchers , 2007 .

[39]  C. Champod,et al.  Multimodal biometrics for identity documents ( ) , 2007 .

[40]  Stephanie Schuckers,et al.  Spoofing and Anti-Spoofing Measures , 2002, Inf. Secur. Tech. Rep..

[41]  N. Jaspen Applied Nonparametric Statistics , 1979 .

[42]  Michael E. Schuckers Using the Beta-Binomial Distribution to Assess Performance of a Biometric Identification Device , 2003, Int. J. Image Graph..

[43]  Ton van der Putte,et al.  Biometrical Fingerprint Recognition: Don't Get Your Fingers Burned , 2001, CARDIS.

[44]  Lin Sun,et al.  Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[45]  Johannes Peltola,et al.  Soft biometrics - combining body weight and fat measurements with fingerprint biometrics , 2006, Pattern Recognit. Lett..

[46]  Douglas A. Reynolds,et al.  A Tutorial on Text-Independent Speaker Verification , 2004, EURASIP J. Adv. Signal Process..

[47]  Patrick J. Flynn,et al.  Empirical Studies of the Existence of the Biometric Menagerie in the FRGC 2.0 Color Image Corpus , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[48]  Andy Adler Sample images can be independently restored from face recognition templates , 2003, CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436).

[49]  P. Ekman,et al.  Facial action coding system: a technique for the measurement of facial movement , 1978 .

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

[51]  Anil K. Jain,et al.  Attacks on biometric systems: a case study in fingerprints , 2004, IS&T/SPIE Electronic Imaging.

[52]  Takeo Kanade,et al.  Computer recognition of human faces , 1980 .

[53]  E. Mayoraz,et al.  Fusion of face and speech data for person identity verification , 1999, IEEE Trans. Neural Networks.

[54]  Patrick J. Flynn,et al.  A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition , 2006, Comput. Vis. Image Underst..

[55]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[56]  David Chandler,et al.  Biometric Product Testing Final Report , 2001 .

[57]  S. Pruzansky Pattern‐Matching Procedure for Automatic Talker Recognition , 1963 .

[58]  Sharath Pankanti,et al.  The relation between the ROC curve and the CMC , 2005, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05).

[59]  E. S. Pearson,et al.  THE USE OF CONFIDENCE OR FIDUCIAL LIMITS ILLUSTRATED IN THE CASE OF THE BINOMIAL , 1934 .

[60]  Richard Youmaran,et al.  Towards a measure of biometric feature information , 2009, Pattern Analysis and Applications.

[61]  P. Jonathon Phillips,et al.  Models of large population recognition performance , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[62]  Sharath Pankanti,et al.  Error analysis of pattern recognition systems - the subsets bootstrap , 2004, Comput. Vis. Image Underst..

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

[64]  L. Brown,et al.  Interval Estimation for a Binomial Proportion , 2001 .

[65]  Patrick J. Flynn,et al.  Visible-light and Infrared Face Recognition , 2003 .

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

[67]  Chris J. Hill,et al.  Risk of Masquerade Arising from the Storage of Biometrics , 2001 .

[68]  Stephanie Schuckers,et al.  Time-series detection of perspiration as a liveness test in fingerprint devices , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).