research-article

Human authentication using finger knuckle print

Authors:

P. Deepa Shenoy,

K. R. Venugopal,

L. M. PatnaikAuthors Info & Claims

COMPUTE '11: Proceedings of the Fourth Annual ACM Bangalore Conference

Article No.: 9, Pages 1 - 8

https://doi.org/10.1145/1980422.1980431

Published: 25 March 2011 Publication History

Abstract

Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like Finger Knuckle Print (FKP) of a person is unique and secure. In this paper, we propose a human authentication system based on FKP image of a person. Depending on the security level required by an organization that implements the proposed system, we provide two modes of security viz. basic mode and advanced mode. The Radon Transform is applied on pre-processed FKP image and Eigen values are computed. For basic mode, we compute the correlation coefficient between the set of Eigen values stored in the database and that of input image to authenticate a person. For advanced level of security, we identify the peak points in Radon graph. The successive distances between those points are calculated and are stored in a vector. Now, the elements in distance vector stored in database and that of input image are compared. Such a match is considered to be success if the difference between two such elements is lesser than the threshold value. Now, the probability of success is computed. To authenticate a person in advanced mode, we use the correlation coefficient between Eigen values and the probability. For real time implementation, suitable GUI can be developed. The basic mode of security system is found to have FAR as 6.79% and FRR as 0.0517%. The advanced system has the FAR of about 1.55% and FRR as 1.02%.

References

[1]

W. Lingyu and G. Leedham. Near and far infrared imaging for vein pattern biometrics. In IEEE Int. Conf. on Video and Signal Based Surveillance (AVSS 06), pages 52--52, November 2006.

Digital Library

[2]

Anil K. Jain, A. Ross, and S. Prabhakar. An introduction to biometric recognition. IEEE Trans. on Circuits Sys., 14(1):4--20, Janaury 2004.

Digital Library

[3]

S. Pankanti, S. Prabhakar, and Anil K Jain. On the individuality of fingerprints. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 805--812, December 2001.

[4]

Chetana Hegde, P Deepa Shenoy, K R Venugopal, and L M Patnaik. Authentication of damaged hand vein patterns by modulerization. In Proc. of IEEE Tenth Region Conference (TENCON 2009), November 2009.

[5]

Chetana Hegde, S Manu, P Deepa Shenoy, K R Venugopal, and L M Patnaik. Secure authentication using image processing and visual cryptography for banking applications. In Proc. of 16th Int. Conf. Advanced Computing (ADCOM 2008), pages 65--72, December 2008.

[6]

W Boles. A security system based on human iris identification using wavelet transforms. In Proc. of 1st Int. Conf. Knowledge-Based Intelligent Electron. Syst., 1997.

[7]

Chetana Hegde, P Deepa Shenoy, K R Venugopal, and L M Patnaik. Ear pattern recognition using centroids and cross-points for robust authentication. In Proc. of 2nd Int. Conf. Intelligent Human and Computer Interaction (IHCI 2010), pages 378--384, January 2010.

[8]

Chetana Hegde, H Rahul Prabhu, D S Sagar, P Deepa Shenoy, K R Venugopal, and L M Patnaik. Human authentication based on ecg waves using radon transform. In Proc. of Int. Conf. Security Technology-Special Session on Biometrics Security and Technology (SecTech-BTS-2010), pages 197--206, December 2010.

[9]

Chetana Hegde, H Rahul Prabhu, D S Sagar, P Deepa Shenoy, K R Venugopal, and L M Patnaik. Statistical analysis for human authentication using ecg waves. In Proc. of 5th Int. Conf. Information Systems, Technology and Management (ICISTM-2011), Accepted.

[10]

D. L. Woodard and P. J. Flynn. Finger surface as a biometric identifier. Computer Vision and Image Understanding, 100(3):357--384, December 2005.

Digital Library

[11]

Ajay Kumar and Yingbo Zhou. Personal identification using finger knuckle orientation features. Electronics Letters, 45(20):1--8, September 2009.

[12]

Ajay Kumar and Ch. Ravikanth. Personal authentication using finger knuckle surface. IEEE Trans Info. Forensics Security, 4(1):98--110, March 2009.

Digital Library

[13]

D. L. Woodard and P. J. Flynn. Personal identification utilizing finger surface features. In Proc. of CVPR-2005, pages 1030--1036, 2005.

Digital Library

[14]

C. Ravikanth and A. Kumar. Biometric authentication using finger-back surface. In Proc. of CVPR-2007, pages 1--6, 2007.

[15]

Lin Zhang, Lei Zhang, David Zhang, and Hailong Zhu. Online finger-knuckle-print verfication for personal authentication. Pattern Recognition, 43(7):2560--2571, July 2010.

Digital Library

[16]

Lin Zhang, Lei Zhang, and David Zhang. Finger-knuckle-print: A new biometric identifier. In Proc. of IEEE Int. Conf. on Image Processing, 2009.

Digital Library

[17]

Lin Zhang, Lei Zhang, and David Zhang. Finger-knuckle-print verification based on band-limited phase-only correlation. In Proc. of 13th Int. Conf. on Computer Analysis of Images and Patterns, pages 141--148, 2009.

Digital Library

[18]

Lin Zhang, Lei Zhang, David Zhang, and Hailong Zhu. Ensemble of local and global information for finger-knuckle-print recognition. Pattern Recognition, accepted.

Digital Library

[19]

Polyu fkp database. http://www.comp.polyu.edu.hk/biometrics/FKP.htm.

[20]

P. Ariyapreechakul and N. Covavisaruch. Personal verification and identification via iris pattern using radon transform. In Proc. of First National Conf. on Computing and Information Technology, pages 287--292, 2005.

Cited By

Jaswal GKaul ANath R(2016)Knuckle Print Biometrics and Fusion Schemes -- Overview, Challenges, and SolutionsACM Computing Surveys10.1145/293872749:2(1-46)Online publication date: 11-Nov-2016
https://dl.acm.org/doi/10.1145/2938727
Usha KEzhilarasan M(2016)Personal recognition using finger knuckle shape oriented features and texture analysisJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2015.02.00428:4(416-431)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.jksuci.2015.02.004
Usha KEzhilarasan M(2015)Finger knuckle biometrics - A reviewComputers and Electrical Engineering10.1016/j.compeleceng.2014.11.00845:C(249-259)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1016/j.compeleceng.2014.11.008
Show More Cited By

Index Terms

Human authentication using finger knuckle print
1. Applied computing
  1. Life and medical sciences
2. Security and privacy
  1. Security services
    1. Authentication
  2. Systems security
    1. Operating systems security

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Published In

cover image ACM Other conferences

COMPUTE '11: Proceedings of the Fourth Annual ACM Bangalore Conference

March 2011

194 pages

ISBN:9781450307505

DOI:10.1145/1980422

Conference Chairs:
R. K. Shyamasundar
TIFR, India
,
Lokendra Shastri
Infosys Labs, Infosys

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 March 2011

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Compute'11

Sponsor:

Compute'11: ACM Bangalore Chapter 4th Annual Conference

March 25 - 26, 2011

Bangalore, India

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Overall Acceptance Rate 114 of 622 submissions, 18%

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Citations

Cited By

Jaswal GKaul ANath R(2016)Knuckle Print Biometrics and Fusion Schemes -- Overview, Challenges, and SolutionsACM Computing Surveys10.1145/293872749:2(1-46)Online publication date: 11-Nov-2016
https://dl.acm.org/doi/10.1145/2938727
Usha KEzhilarasan M(2016)Personal recognition using finger knuckle shape oriented features and texture analysisJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2015.02.00428:4(416-431)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.jksuci.2015.02.004
Usha KEzhilarasan M(2015)Finger knuckle biometrics - A reviewComputers and Electrical Engineering10.1016/j.compeleceng.2014.11.00845:C(249-259)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1016/j.compeleceng.2014.11.008
Usha KEzhilarasan M(2014)Haar-Wavelet Transform based finger knukle print recognition2014 International Conference on Recent Trends in Information Technology10.1109/ICRTIT.2014.6996141(1-6)Online publication date: Apr-2014
https://doi.org/10.1109/ICRTIT.2014.6996141
Usha KEzhilarasan M(2014)Contourlet Transform Based Feature Extraction Method for Finger Knuckle Recognition SystemComputational Intelligence in Data Mining - Volume 310.1007/978-81-322-2202-6_37(407-416)Online publication date: 12-Dec-2014
https://doi.org/10.1007/978-81-322-2202-6_37
Hegde CShenoy PVenugopal KPatnaik L(2013)Authentication using Finger Knuckle PrintsSignal, Image and Video Processing10.1007/s11760-013-0469-77:4(633-645)Online publication date: 19-Apr-2013
https://doi.org/10.1007/s11760-013-0469-7
Hegde CShenoy PVenugopal KPatnaik L(2011)FKP biometrics for human authentication using Gabor WaveletsTENCON 2011 - 2011 IEEE Region 10 Conference10.1109/TENCON.2011.6129292(1149-1153)Online publication date: Nov-2011
https://doi.org/10.1109/TENCON.2011.6129292

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