ARTeM: a new system for human authentication using finger vein images

A new system (ARTeM) for human authentication using finger vein images is described here. The developed algorithm combines 1) a fuzzy contrast enhancement algorithm with 2) a mutual information and affine transformation based registration technique and 3) a correlation coefficient based template matching algorithm, to detect the identity of a person based on the match-scores with finger vein images stored in the database. For performance assessment of the ARTeM algorithm, the benchmark SDUMLA multimodal biometric database containing 3816 images of 106 persons is used. On the complete database, up to 95.28% classification accuracy is achieved with single finger images; while up to 98.11% accuracy is observed with a consensus of two fingers. On a reduced subset of 86 persons’ database, 98.84% accuracy is achieved with single finger classification and cent percent classification is obtained using a consensus of two fingers. Comparative analyses with other works also validate the effectiveness of the developed methodology.

[1]  Arun Ross,et al.  50 years of biometric research: Accomplishments, challenges, and opportunities , 2016, Pattern Recognit. Lett..

[2]  R.A. Rashid,et al.  Security system using biometric technology: Design and implementation of Voice Recognition System (VRS) , 2008, 2008 International Conference on Computer and Communication Engineering.

[3]  David Zhang,et al.  Online Palmprint Identification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Naoto Miura,et al.  Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles , 2007, MVA.

[5]  Ajay Kumar,et al.  Personal Authentication Using Hand Vein Triangulation and Knuckle Shape , 2009, IEEE Transactions on Image Processing.

[6]  Zhihan Lv,et al.  Stereoscopic image quality assessment method based on binocular combination saliency model , 2016, Signal Process..

[7]  Anil K. Jain,et al.  Handbook of Face Recognition, 2nd Edition , 2011 .

[8]  Sang Min Yoon,et al.  Illumination Normalization for SIFT Based Finger Vein Authentication , 2012, ISVC.

[9]  Dong Sun Park,et al.  Finger Vein Recognition based on Matching Score-Level Fusion of Gabor Features , 2013 .

[10]  Bo-Chao Cheng,et al.  Special point representations for reducing data space requirements of finger-vein recognition applications , 2016, Multimedia Tools and Applications.

[11]  Lingyu Wang,et al.  Minutiae feature analysis for infrared hand vein pattern biometrics , 2008, Pattern Recognit..

[12]  Wenxin Li,et al.  The ICB-2015 Competition on Finger Vein Recognition , 2015, 2015 International Conference on Biometrics (ICB).

[13]  Yilong Yin,et al.  SDUMLA-HMT: A Multimodal Biometric Database , 2011, CCBR.

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

[15]  Jian-Da Wu,et al.  Driver identification using finger-vein patterns with Radon transform and neural network , 2009, Expert Syst. Appl..

[16]  Riza Sulaiman,et al.  Review on finger vein authentication system by applying neural network , 2010, 2010 International Symposium on Information Technology.

[17]  Xiao Han,et al.  Multiscale Feature Extraction of Finger-Vein Patterns Based on Curvelets and Local Interconnection Structure Neural Network , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[18]  Eui Chul Lee,et al.  New Finger Biometric Method Using Near Infrared Imaging , 2011, Sensors.

[19]  Madasu Hanmandlu,et al.  Score level fusion of multimodal biometrics using triangular norms , 2011, Pattern Recognit. Lett..

[20]  Zhihan Lv,et al.  Iterative quadtree decomposition based automatic selection of the seed point for ultrasound breast tumor images , 2016, Multimedia Tools and Applications.

[21]  Yanzhe Cui,et al.  Finger-vein image recognition combining modified Hausdorff distance with minutiae feature matching , 2009, Interdisciplinary Sciences: Computational Life Sciences.

[22]  Shahrel Azmin Suandi,et al.  Finger Vein Recognition Using Local Line Binary Pattern , 2011, Sensors.

[23]  Dayong Wang,et al.  Local SIFT analysis for hand vein pattern verification , 2009, International Conference on Optical Instruments and Technology.

[24]  Hans-Paul Schwefel,et al.  Evolution strategies – A comprehensive introduction , 2002, Natural Computing.

[25]  K. R. Park.  Finger Vein Recognition by Combining Global and Local Features based on SVM , 2011, Comput. Informatics.

[26]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[27]  Mojgan Mahdavi Zadeh,et al.  A comparative study on , 2014 .

[28]  Mehdi Nasri,et al.  A multibiometric finger vein verification system based on score level fusion strategy , 2015, 2015 International Congress on Technology, Communication and Knowledge (ICTCK).

[29]  Bakhtiar Affendi Rosdi,et al.  Finger-vein identification using pattern map and principal component analysis , 2011, 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA).

[30]  MITCHELL TRAURING,et al.  Automatic Comparison of Finger-Ridge Patterns , 1963, Nature.

[31]  Federica Marcolin,et al.  3D face recognition: An automatic strategy based on geometrical descriptors and landmarks , 2014, Robotics Auton. Syst..

[32]  Naoto Miura,et al.  Feature Extraction of Finger-vein Patterns Based on Repeated Line Tracking and Its Application to Personal Identification , 2022 .

[33]  M. Bhavani.  Human Identification Using Finger and Iris Images , 2013 .

[34]  Ju Cheng Yang,et al.  Robust Finger Vein ROI Localization Based on Flexible Segmentation , 2013, Sensors.

[35]  Zhihan Lv,et al.  Game On, Science - How Video Game Technology May Help Biologists Tackle Visualization Challenges , 2013, PloS one.

[36]  Sébastien Marcel,et al.  On the vulnerability of finger vein recognition to spoofing , 2014, 2014 International Conference of the Biometrics Special Interest Group (BIOSIG).

[37]  Ronald R. Coifman,et al.  Entropy-based algorithms for best basis selection , 1992, IEEE Trans. Inf. Theory.

[38]  Martin Styner,et al.  Parametric estimate of intensity inhomogeneities applied to MRI , 2000, IEEE Transactions on Medical Imaging.

[39]  Karim Faez,et al.  An Efficient Dorsal Hand Vein Recognition Based on Firefly Algorithm , 2013 .

[40]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[41]  Paul Suetens,et al.  Non-rigid Multimodal Image Registration Using Mutual Information , 1998, MICCAI.

[42]  David R. Haynor,et al.  Nonrigid multimodality image registration , 2001, SPIE Medical Imaging.

[43]  Arun Ross,et al.  A survey on ear biometrics , 2013, CSUR.

[44]  John Daugman,et al.  How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.

[45]  Wei-Yun Yau,et al.  Person recognition by fusing palmprint and palm vein images based on "Laplacianpalm" representation , 2008, Pattern Recognit..

[46]  Pedro Tome,et al.  Cross-database evaluation using an open finger vein sensor , 2014, 2014 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS) Proceedings.

[47]  Sankar Kumar Pal.  Studies on the application of fuzzy set theoretic approach in some problems of pattern recognition and man machine communication by voice , 1978 .

[48]  Woo Chaw Seng,et al.  A review of biometric technology along with trends and prospects , 2014, Pattern Recognit..

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

[50]  Jinfeng Yang,et al.  Finger-vein ROI localization and vein ridge enhancement , 2012, Pattern Recognit. Lett..

[51]  Qingmin Liao,et al.  Personal Identification for Single Sample Using Finger Vein Location and Direction Coding , 2011, 2011 International Conference on Hand-Based Biometrics.

[52]  M. Akila,et al.  Biometric personal authentication using keystroke dynamics: A review , 2011, Appl. Soft Comput..

[53]  Weifeng Li,et al.  Finger Vein Verification Based on Neighbor Pattern Coding , 2013, IEICE Trans. Inf. Syst..

[54]  Anil K. Jain,et al.  A modified Hausdorff distance for object matching , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[55]  Zhihan Lv,et al.  Multimodal Hand and Foot Gesture Interaction for Handheld Devices , 2014, TOMM.

[56]  Jinfeng Yang,et al.  Multi-Channel Gabor Filter Design for Finger-Vein Image Enhancement , 2009, 2009 Fifth International Conference on Image and Graphics.

[57]  Christophe Rosenberger,et al.  Palm Vein Verification System Based on SIFT Matching , 2009, ICB.

[58]  Yajie Tian,et al.  Handbook of face recognition , 2003 .

[59]  Arun Ross,et al.  Periocular Biometrics in the Visible Spectrum , 2011, IEEE Transactions on Information Forensics and Security.

[60]  Dorra Sellami,et al.  A New Multimodal Biometric System Based on Finger Vein and Hand Vein Recognition , 2013 .

[61]  Zhihan Lv,et al.  Imagining in-air interaction for hemiplegia sufferer , 2015, 2015 International Conference on Virtual Rehabilitation (ICVR).

[62]  Ajay Kumar,et al.  Human Identification Using Finger Images , 2012, IEEE Transactions on Image Processing.

[63]  S. Pal,et al.  Image enhancement using smoothing with fuzzy sets , 1981 .

[64]  Purkar Rohini Uttam,et al.  Palm Vein Authentication , 2009, Encyclopedia of Biometrics.

[65]  Jian Yang,et al.  A Two-Phase Test Sample Sparse Representation Method for Use With Face Recognition , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

[66]  Baihua Li,et al.  Quality assessment metric of stereo images considering cyclopean integration and visual saliency , 2016, Inf. Sci..

[67]  T. Ohyama,et al.  Human finger vein images are diverse and its patterns are useful for personal identification , 2007 .

[68]  Sharath Pankanti,et al.  Biometrics: Personal Identification in Networked Society , 2013 .

[69]  D. Mulyono,et al.  A study of finger vein biometric for personal identification , 2008, 2008 International Symposium on Biometrics and Security Technologies.