Indexing Techniques for Fingerprint and Iris Databases

Indexing Techniques for Fingerprint and Iris Databases by Rajiv Mukherjee Master of Science in Electrical Engineering West Virginia University Arun Ross, Ph.D., Chair This thesis addresses the problem of biometric indexing in the context of fingerprint and iris databases. In large scale authentication system, the goal is to determine the identity of a subject from a large set of identities. Indexing is a technique to reduce the number of candidate identities to be considered by the identification algorithm. The fingerprint indexing technique (for closed set identification) proposed in this thesis is based on a combination of minutiae and ridge features. Experiments conducted on the FVC2002 and FVC2004 databases indicate that the inclusion of ridge features aids in enhancing indexing performance. The thesis also proposes three techniques for iris indexing (for closed set identification). The first technique is based on iriscodes. The second technique utilizes local binary patterns in the iris texture. The third technique analyzes the iris texture based on a pixel-level difference histogram. The ability to perform indexing at the texture level avoids the computational complexity involved in encoding and is, therefore, more attractive for iris indexing. Experiments on the CASIA 3.0 database suggest the potential of these schemes to index large-scale iris databases. 3 I dedicate my thesis to my family

[1]  Y. S. Moon,et al.  Wavelet based fingerprint liveness detection , 2005 .

[2]  Steven Fortune,et al.  A sweepline algorithm for Voronoi diagrams , 1986, SCG '86.

[3]  Anil K. Jain,et al.  A Real-Time Matching System for Large Fingerprint Databases , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

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

[5]  A. Ganson.  Fingerprint Classification , 1970, Nature.

[6]  Dexin Zhang,et al.  Efficient iris recognition by characterizing key local variations , 2004, IEEE Transactions on Image Processing.

[7]  Bir Bhanu,et al.  Fingerprint Indexing Based on Novel Features of Minutiae Triplets , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  King-Sun Fu,et al.  A syntactic approach to fingerprint pattern recognition , 1975, Pattern Recognit..

[9]  Stephanie Schuckers,et al.  Active shape models for effective iris segmentation , 2006, SPIE Defense + Commercial Sensing.

[10]  Ajai Jain,et al.  The Handbook of Pattern Recognition and Computer Vision , 1993 .

[11]  Junzhou Huang,et al.  Iris Model Based on Local Orientation Description , 2004 .

[12]  Michael Boyd,et al.  Iris Recognition , 2006 .

[13]  Okhwan Byeon,et al.  Efficient Iris Recognition through Improvement of Feature Vector and Classifier , 2001 .

[14]  Tieniu Tan,et al.  A new iris segmentation method for recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[15]  Lindsay I. Smith,et al.  A tutorial on Principal Components Analysis , 2002 .

[16]  Stephanie Schuckers,et al.  Fingerprint Liveness Detection Using Local Ridge Frequencies and Multiresolution Texture Analysis Techniques , 2006, 2006 International Conference on Image Processing.

[17]  George Bebis,et al.  Fingerprint identification using Delaunay triangulation , 1999, Proceedings 1999 International Conference on Information Intelligence and Systems (Cat. No.PR00446).

[18]  Tetsuo Asano,et al.  Distorted Fingerprint Indexing Using Minutia Detail and Delaunay Triangle , 2006, 2006 3rd International Symposium on Voronoi Diagrams in Science and Engineering.

[19]  A. Senior,et al.  A hidden Markov model fingerprint classifier , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[20]  Isidore Rigoutsos,et al.  FLASH: a fast look-up algorithm for string homology , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[21]  David P. Dobkin,et al.  The quickhull algorithm for convex hulls , 1996, TOMS.

[22]  Robert K. L. Gay,et al.  Geometric framework for fingerprint image classification , 1997, Pattern Recognit..

[23]  Jonathan Richard Shewchuk,et al.  Triangle: Engineering a 2D Quality Mesh Generator and Delaunay Triangulator , 1996, WACG.

[24]  Haim J. Wolfson,et al.  Geometric hashing: an overview , 1997 .

[25]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[26]  Dinesh Manocha,et al.  Applied Computational Geometry Towards Geometric Engineering , 1996, Lecture Notes in Computer Science.

[27]  Arun Ross,et al.  A calibration model for fingerprint sensor interoperability , 2006, SPIE Defense + Commercial Sensing.

[28]  G. Annas.  HIPAA regulations - a new era of medical-record privacy? , 2003, The New England journal of medicine.

[29]  Anil K. Jain,et al.  Soft Biometric Traits for Personal Recognition Systems , 2004, ICBA.

[30]  Arun Ross,et al.  An introduction to biometric recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[31]  Arun Ross,et al.  Handbook of Multibiometrics , 2006, The Kluwer international series on biometrics.

[32]  Boualem Boashash,et al.  A human identification technique using images of the iris and wavelet transform , 1998, IEEE Trans. Signal Process..

[33]  Tieniu Tan,et al.  Graph Matching Iris Image Blocks with Local Binary Pattern , 2006, ICB.

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

[35]  John Daugman,et al.  Demodulation by Complex-Valued Wavelets for Stochastic Pattern Recognition , 2003, Int. J. Wavelets Multiresolution Inf. Process..

[36]  John Daugman,et al.  High Confidence Visual Recognition of Persons by a Test of Statistical Independence , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Robert S. Germain,et al.  Fingerprint matching using transformation parameter clustering , 1997 .

[38]  Keith A. Rhodes.  Testimony Before the Subcommittee on Aviation , Committee on Transportation and Infrastructure , House of Representatives United States , 2004 .

[39]  Tieniu Tan,et al.  Iris recognition using circular symmetric filters , 2002, Object recognition supported by user interaction for service robots.

[40]  M. Lynch,et al.  The similarity index and DNA fingerprinting. , 1990, Molecular biology and evolution.

[41]  D. T. Lee,et al.  Two algorithms for constructing a Delaunay triangulation , 1980, International Journal of Computer & Information Sciences.

[42]  Natalia A. Schmid,et al.  Performance evaluation of iris-based recognition system implementing PCA and ICA encoding techniques , 2005, SPIE Defense + Commercial Sensing.

[43]  Richard P. Wildes,et al.  A system for automated iris recognition , 1994, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision.

[44]  S. Liu,et al.  A practical guide to biometric security technology , 2001 .

[45]  Arun Ross,et al.  Augmenting ridge curves with minutiae triplets for fingerprint indexing , 2007, SPIE Defense + Commercial Sensing.

[46]  Dexin Zhang,et al.  Personal Identification Based on Iris Texture Analysis , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[47]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[48]  Peter Kovesi,et al.  MATLAB Functions for Computer Vision and Image Analysis , 2004 .

[49]  Jaihie Kim,et al.  Iris Feature Extraction Using Independent Component Analysis , 2003, AVBPA.

[50]  Ugur Halici,et al.  Fingerprint classification through self-organizing feature maps modified to treat uncertainties , 1996, Proc. IEEE.

[51]  Pengfei Shi,et al.  Iris Feature Extraction Using 2D Phase Congruency , 2005, Third International Conference on Information Technology and Applications (ICITA'05).

[52]  Topi Mäenpää,et al.  The local binary pattern approach to texture analysis - extensions and applications , 2003 .

[53]  Stephanie Schuckers,et al.  Biorthogonal-wavelets-based iris recognition , 2005, SPIE Defense + Commercial Sensing.

[54]  B. V. K. Vijaya Kumar,et al.  Robust Iris Recognition Using Advanced Correlation Techniques , 2005, ICIAR.

[55]  Ashok A. Ghatol,et al.  Iris recognition: an emerging biometric technology , 2007 .