Finger Knuckle Print Identification with Hierarchical Model of Local Gradient Features

In this paper we present new biologically inspired method for biometric human identification based on the knuckle finger print (FKP). Knuckle is a part of hand, and therefore, is easily accessible, invariant to emotions and other behavioral aspects (e.g. tiredness) and most importantly is rich in texture features which usually are very distinctive. The proposed method is based on the hierarchical feature extraction model. We also showed the results obtained for PolyU knuckle image database.

[1]  Connie Tee,et al.  BI-MODAL PALM PRINT AND KNUCKLE PRINT RECOGNITION SYSTEM , 2016 .

[2]  M. Choras,et al.  Emerging Methods of Biometrics Human Identification , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[3]  Karim Faez,et al.  A novel approach for Finger-Knuckle-Print recognition based on Gabor feature fusion , 2011, 2011 4th International Congress on Image and Signal Processing.

[4]  D. Hubel,et al.  Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.

[5]  Miguel A. Ferrer,et al.  Improved finger-knuckle-print authentication based on orientation enhancement , 2011 .

[6]  T. Poggio,et al.  Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.

[7]  Alice Caplier,et al.  Using Human Visual System modeling for bio-inspired low level image processing , 2010, Comput. Vis. Image Underst..

[8]  Tee Connie,et al.  An innovative contactless palm print and knuckle print recognition system , 2010 .

[9]  M. Choraś.  Novel technigues applied to biometric human identification , 2009 .

[10]  David Zhang,et al.  Ensemble of local and global information for finger-knuckle-print recognition , 2011, Pattern Recognit..

[11]  Ahmed Bouridane,et al.  Palmprint and Finger-Knuckle-Print for efficient person recognition based on Log-Gabor filter response , 2011 .

[12]  Ajay Kumar,et al.  Personal Authentication Using Finger Knuckle Surface , 2009, IEEE Transactions on Information Forensics and Security.

[13]  Phalguni Gupta,et al.  An Efficient Finger-Knuckle-Print Based Recognition System Fusing SIFT and SURF Matching Scores , 2011, ICICS.

[14]  Changyin Sun,et al.  Finger-knuckle-print recognition using Gabor feature and MMDA , 2011, Proceedings of the 30th Chinese Control Conference.

[15]  Jianying Zhou,et al.  Information and Communications Security , 2013, Lecture Notes in Computer Science.

[16]  Baptiste Hemery,et al.  Sift Based Recognition of Finger Knuckle Print , 2010, ISC 2010.

[17]  David G. Lowe,et al.  University of British Columbia. , 1945, Canadian Medical Association journal.

[18]  R. Kozik.  A proposal of biologically inspired hierarchical approach to object recognition , 2013 .

[19]  Michal Choras,et al.  Knuckle Biometrics Based on Texture Features , 2010, 2010 International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics.

[20]  Koichi Ito,et al.  Finger-Knuckle-Print recognition using BLPOC-based local block matching , 2011, The First Asian Conference on Pattern Recognition.

[21]  Changyin Sun,et al.  Finger-Knuckle-Print Recognition Using LGBP , 2011, ISNN.

[22]  Haibo He,et al.  Advances in Neural Networks - ISNN 2011 - 8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, May 29-June 1, 2011, Proceedings, Part I , 2011, International Symposium on Neural Networks.

[23]  David Zhang,et al.  Online finger-knuckle-print verification for personal authentication , 2010, Pattern Recognit..

[24]  David Zhang,et al.  Finger-Knuckle-Print Verification Based on Band-Limited Phase-Only Correlation , 2009, CAIP.