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Finger Knuckle Print Identification using Gabor Features

by Shubhangi Neware, Kamal Mehta, A. S. Zadgaonkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 18
Year of Publication: 2014
Authors: Shubhangi Neware, Kamal Mehta, A. S. Zadgaonkar
10.5120/17283-7641

Shubhangi Neware, Kamal Mehta, A. S. Zadgaonkar . Finger Knuckle Print Identification using Gabor Features. International Journal of Computer Applications. 98, 18 ( July 2014), 22-24. DOI=10.5120/17283-7641

@article{ 10.5120/17283-7641,
author = { Shubhangi Neware, Kamal Mehta, A. S. Zadgaonkar },
title = { Finger Knuckle Print Identification using Gabor Features },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 98 },
number = { 18 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 22-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number18/17283-7641/ },
doi = { 10.5120/17283-7641 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:26:31.649543+05:30
%A Shubhangi Neware
%A Kamal Mehta
%A A. S. Zadgaonkar
%T Finger Knuckle Print Identification using Gabor Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 18
%P 22-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the current trends in biometric human identification is the development of new emerging modalities. Knuckle biometrics is one of such promising modalities. Texture pattern produced by the finger knuckle bending is highly unique and makes the surface a distinctive biometric identifier. This paper presents feature based identification methods for an emerging biometric identifier called Finger-Knuckle-Print (FKP). Techniques employed for feature based approach is Gabor filter method .In applications of computer vision and image analysis, Gabor filters have maintained their popularity in feature extraction for almost three decades. In the proposed work experiment is carried out to identify finger knuckle images of more than 100 persons. Compared with the other existing finger back surface based biometric system, the proposed FKP system achieves much higher recognition rate.

References
  1. Jain, A.K., Flynn, P., Ross, A. (eds.): Handbook of Biometrics. Springer, Heidelberg(2007)
  2. Kumar A and Ravikanth C, “Personal authentication using finger knuckle surface”, IEEE Transactions on Information Forensics and Security, 4(1):98 –110, 2009.
  3. Badrinath G S, Nigam A. and Gupta P, “An Efficient Finger-knuckle-print based Recognition System Fusing SIFT and SURF Matching Scores”, Information and communication Security, pp374-387, 2011..Woodard D.L., Flynn P.J., “Finger surface as a biometric identifier”, CVIU, vol. 100, pp. 357–384, 2005.
  4. D. Gabor, Theory of communication, Journal of the Institute of Electrical Engineers 93 (1946) 429-457.
  5. L. Nanni, A. Lumini, On selecting Gabor features for biometric authentication, International Journal of Computer Applications in Technology 35 (1) (2009) 23-28.
  6. A. Kong, An evaluation of Gabor orientation as a feature for face recognition, in: Proceedings of ICPR’08,2008.
  7. Zhang L, Zhang L, Zhang D, “Finger-Knuckle Print: A New Biometric Identifier”, Image Processing ICIP, IEEE International Conference, pp1981-84, Nov2009.
  8. T.S. Lee, Image representation using 2D Gabor wavelet, IEEE Trans. Pattern Analysis and Machine Intelligence18 (10) (1996) 957-971.
  9. http://www4.comp.polyu.edu.hk/~CSajaykr/IITD/iitd_knuckle.htm
  10. Kumar A and Zhou Y, “Human identification using knuckle codes”, Proceedings BTAS, Washington, 2009.
  11. Neware S, Mehta K, Zadgaonkar A , “Finger Knuckle Identification using Principal Component Analysis and Nearest Mean Classifier”, International Journal of Computer Applications (0975 – 8887) Volume 70– No.9, May 2013 .
  12. Woodard D.L., Flynn P.J., “Finger surface as a biometric identifier”, CVIU, vol. 100, pp. 357–384, 2005.
  13. Zhang L, Zhang L, Zhang D, Zhu H,“Ensemble of local and global information for finger-knuckle-print recognition”, Pattern Recognition, 44(9):1990 – 1998, 2011.
  14. Shoichiro A, Koichi I, Takafumi A, “Finger-Knuckle-Print Recognition Using BLPOC-Based Local Block Matching”, IEEE, 2011.
  15. Rui Z, Tao L, Shunyan H, Jianying S, “ A Novel Approach of Personal Identification Based on the Fusion of Multifinger Knuckleprints”, Advances in information Sciences and Service Sciences(AISS) Volume3, Number10,November 2011.
  16. Kanta Ratha N, Bolle R, “Automatic Fingerprint Recognition System”, Springer, pp17-18.
  17. Gupta P, Rattani A, Mehrotra H, Kaushik A, “Multimodal biometrics system for efficient human Recognition”, Biometric Technique for human Identification III,Proceedings of SPIE,Apr.2006.
  18. Choras M, Kazil R, “Knuckle Biometrics Based on Texture Features”, International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics (ETCHB), IEEE, 2010.
  19. Kumar A, Zhou Y, “Personal Identification using Finger Knuckle Orientation Features”, Electronics Letters ,vol. 45, no. 20, September 2009.
  20. Kumar A, Ch Ravikanth, “Biometric Authentication Using Finger Back Surface”, Computer Vision and Pattern Recognition, IEEE Conference, pp1-6, June2007.
  21. Zhang L, Zhang L, Zhang D, “Finger-Knuckle-Print Verification Based on Band-Limited Phase-Only Correlation”, Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns, pp. 141-148,Springer, 2009.
  22. Jain A, Kumar A, “Biometrics of Next Generation: An Overview”, Second Generation Biometrics, Springer, 2010.
  23. Turk,M. and A. Pentland, Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 3(1),1991,71-86
  24. Neware S, Mehta K, Zadgaonkar, “Finger Knuckle Surface Biometrics”, International Journal of Emerging Technology and Advanced Engineering ,ISSN 2250-2459, Volume 2, Issue 12, December 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Gabor filter Personal authentication

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