Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology


Multimodal Biometric Cryptosystem for Face and Ear Recognition Based on Fuzzy Vault

1Gandhimathi Amirthalingam and 2G. Radhamani
1Department of Computer Science, Bharathiar University, India
2Department of Computer Science, G.R. Damodaran College of Science, India
Research Journal of Applied Sciences, Engineering and Technology  2014  20:4211-4219
http://dx.doi.org/10.19026/rjaset.7.791  |  © The Author(s) 2014
Received: November 11, 2013  |  Accepted: January 01, 2014  |  Published: May 20, 2014

Abstract

Multimodal biometrics technology that uses more than two sorts of biometrics data has been universally applied for person certification and proof. Researchers have advised that the ear may have benefits over the face for biometric recognition. In this study, a technique for face and ear recognition has suggested. The face image and ear images are prearranged as input. From the pre-processed input images, the shape and texture characteristics are removed. The shape of ear and face is attained by suggesting modified region growing algorithm and texture characteristic by Local Gabor XOR Pattern (LGXP) method. To produce the fuzzy vault, the multi-modal biometric template and the input key are employed. For working out, the multi-modal biometric template from face and ear will be erected and it is united with the stored fuzzy vault to produce the final key. Experimental results of suggested method explain promising development in multimodal biometric validation.

Keywords:

Biometric recognition, fuzzy vault, LGXP, modified region growing algorithm, multimodal biometrics,


References

  1. Ahmad, M.I., W.L. Woo and S.S. Dlay, 2010. Multimodal biometric fusion at feature level: Face and palmprint. Proceeding of the 7th International Symposium on Communication Systems Networks and Digital Signal Processing (CSNDSP), pp: 801-805.
  2. Basha, A.J., V. Palanisamy and T. Purusothaman, 2010. Fast multimodal biometric approach using dynamic fingerprint authentication and enhanced iris features. Proceeding of the IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp: 1-6.
    CrossRef    
  3. Chan, T.S. and A. Kumar, 2012. Reliable ear identification using 2-D quadrature filters. Pattern Recog. Lett., 33(14): 1870-1881.
    CrossRef    
  4. Chin, Y.J., T.S. Ong, A. Teoh and K.O. Michael Goh, 2011. Multimodal biometrics based bit extraction method for template security. Proceeding of 6th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp: 1971-1976.
    CrossRef    
  5. Choi, H. and M. Shin, 2009. Learning radial basis function model with matching score quality for person authentication in multimodal biometrics. Proceeding of 1st Asian IEEE Conference on Intelligent Information and Database Systems, pp: 346-350.
    CrossRef    
  6. Dahel, S.K. and Q. Xiao, 2003. Accuracy performance analysis of multimodal biometrics. Proceeding of the IEEE Systems, Man and Cybernetics Society Information Assurance Workshop, pp: 170-173.
    CrossRef    
  7. Gudavalli, M., A.V. Babu, S.V. Raju and D.S. Kumar, 2012. Multimodal biometrics-sources, architecture and fusion techniques: An overview. Proceeding of IEEE International Symposium on Biometrics and Security Technologies, pp: 27-34.
    CrossRef    
  8. Hanmandlu, M., J. Grover, A. Gureja and H.M. Gupta, 2011. Score level fusion of multimodal biometrics using triangular norms. Pattern Recogn. Lett., 32(14): 1843-1850.
    CrossRef    
  9. He, M., S.J. Horng, P. Fan, R.S. Run, R.J. Chen, J.L. Lai, M.K. Khan and K.O. Sentosa, 2010. Performance evaluation of score level fusion in multimodal biometric systems. Pattern Recogn., 43(5): 1789-1800.
    CrossRef    
  10. Huang, H., J. Liu, H. Feng and T. He, 2011. Ear recognition based on uncorrelated local fisher discriminant analysis. Neurocomputing, 74(17): 3103-3113.
    CrossRef    
  11. Huang, Z., Y. Liu, C. Li, M. Yang and L. Chen, 2013. A robust face and ear based multimodal biometric system using sparse representation. Pattern Recogn., 46(8): 2156-2168.
    CrossRef    
  12. Ichino, M., H. Sakano and N. Komatsu, 2006. Multimodal biometrics of lip movements and voice using kernel fisher discriminant analysis. Proceeding of the 9th International Conference on Control, Automation, Robotics and Vision (ICARCV '06), pp: 1-6.
    CrossRef    
  13. Islam, S.M.S., R. Davies, M. Bennamoun, R.A. Owens and A.S. Mian, 2013. Multibiometric human recognition using 3D ear and face features. Pattern Recogn., 46(3): 613-627.
    CrossRef    
  14. Khan, M.K. and J. Zhang, 2008. Multimodal face and fingerprint biometrics authentication on space-limited tokens. Neurocomputing, 17(12): 3026-3031.
    CrossRef    
  15. Kumar, A. and T.S.T. Chan 2013. Robust ear identification using sparse representation of local texture descriptors. Pattern Recogn., 46(1): 73-85.
    CrossRef    
  16. Maple, C. and V. Schetinin, 2006. Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics. Proceeding of the 1st IEEE International Conference on Availability, Reliability and Security, pp: 929-935.
    CrossRef    
  17. Monwar, M.M. and M.L. Gavrilova, 2009. Multimodal biometric system using rank-level fusion approach. IEEE T. Syst. Man Cyb., 39(4): 867-878.
    CrossRef    PMid:19336340    
  18. Pflug, A. and C. Busch, 2012. Ear biometrics: A survey of detection, feature extraction and recognition methods. IET Biometrics, 1(2): 114-129.
    CrossRef    
  19. Raghavendra, R., M. Imran, A. Rao and G. Hemantha Kumar, 2010. Multimodal biometrics: Analysis of Handvein and Palmprint combination used for person verification. Proceeding of 3rd IEEE International Conference on Emerging Trends in Engineering and Technology, pp: 526-530.
  20. Rahman, M.M., M.R. Islam, N.I. Bhuiyan, B. Ahmed and M.A. Islam, 2007. Person identification using ear biometrics. Int. J. Comput. Internet Manage., 15(2): 1-8.
  21. Ross, A. and A.K. Jain, 2004. Multimodal biometrics: An overview. Proceeding of 12th European Signal Processing Conference (EUSIPCO), 14: 1221-1224.
    PMid:14982620    
  22. Ross, A. and A. Abaza, 2011. Human ear recognition. IEEE Comput. Mag., 44(11): 718-737.
    CrossRef    
  23. Wang, D., J. Li and G. Memik, 2009. Authentication scheme of DRM system for remote users based on multimodal biometrics, watermarking and smart cards. Proceeding of the WRI Global Congress on Intelligent Systems (GCIS '09), 2: 530-534.
    CrossRef    
  24. Yang, J., 2010. Biometrics verification techniques combing with digital signature for multimodal biometrics payment system. Proceeding of IEEE 4th International Conference on Management of e-Commerce and e-Government, pp: 405-410.
    CrossRef    
  25. Yaoa, Y.F., X.Y. Jing and H.S. Wong, 2007. Face and palm print feature level fusion for single sample biometrics recognition. Neurocomputing, 9(8).
  26. Yuan, L. and Z.C. Mu, 2012. Ear recognition based on local information fusion. Pattern Recogn. Lett., 33(2): 182-190.
    CrossRef    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved