Table of Contents Author Guidelines Submit a Manuscript
Computational Intelligence and Neuroscience
Volume 2017, Article ID 9345969, 9 pages
https://doi.org/10.1155/2017/9345969
Research Article

Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion

1Computer Science Department, University of Lac Hong, Dong Nai 810000, Vietnam
2Computer Science Department, VNUHCM-University of Science, Ho Chi Minh City 700000, Vietnam

Correspondence should be addressed to Thai Hoang Le; nv.ude.sumch.tif@iahthl

Received 3 May 2017; Revised 14 August 2017; Accepted 24 September 2017; Published 31 October 2017

Academic Editor: George A. Papakostas

Copyright © 2017 Long Binh Tran and Thai Hoang Le. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. K. Jain, P. Flynn, and A. A. Ross, Handbook of Biometrics, Springer, 2008. View at Publisher · View at Google Scholar
  2. D. Jagadiswary and D. Saraswady, “Biometric authentication using fused multimodal biometric,” in Proceedings of the International Conference on Computational Modelling and Security, CMS 2016, pp. 109–116, India, February 2016. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Ross and A. Jain, “Information fusion in biometrics,” Pattern Recognition Letters, vol. 24, no. 13, pp. 2115–2125, 2003. View at Publisher · View at Google Scholar · View at Scopus
  4. N. Hezil and A. Boukrouche, “Multimodal biometric recognition using human ear and palmprint,” IET Biometrics Journal, vol. 6, no. 5, pp. 351–359, 2017. View at Publisher · View at Google Scholar
  5. R. Parkavi, K. R. C. Babu, and J. A. Kumar, “Multimodal biometrics for user authentication,” in Proceedings of the 2017 11th International Conference on Intelligent Systems and Control, ISCO 2017, pp. 501–505, India, January 2017. View at Publisher · View at Google Scholar · View at Scopus
  6. L. Nanni, A. Lumini, M. Ferrara, and R. Cappelli, “Combining biometric matchers by means of machine learning and statistical approaches,” Neurocomputing, vol. 149, pp. 526–535, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. A. Lumini and L. Nanni, “Overview of the combination of biometric matchers,” Information Fusion, vol. 33, pp. 71–85, 2017. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Jaina, K. Nandakumara, and A. Rossb, “Score normalization in multimodal biometric systems,” Pattern Recognition, vol. 38, no. 12, pp. 2270–2285, 2005. View at Publisher · View at Google Scholar
  9. Y. Ma, B. Cukic, and H. Singh, “A classification approach to multibiometric score fusion,” in Proceedings of Fifth International Conference on AVBPA, pp. 484–493, New York, NY, USA, 2005.
  10. L. B. Tran and T. H. Le, “Personal Authentication Using Relevance Vector Machine (RVM) for Biometric Match Score Fusion,” in Proceedings of the 7th IEEE International Conference on Knowledge and Systems Engineering, KSE 2015, pp. 7–12, Vietnam, October 2015. View at Publisher · View at Google Scholar · View at Scopus
  11. S. C. Dass, K. Nandakumar, and A. K. Jain, “A principled approach to score level fusion in multimodal biometric systems,” in Proceedings of the Audio- and Video-Based Biometric Person Authentication, AVBPA ’05, pp. 1049–1058, 2005.
  12. K. Nandakumar, Multibiometric Systems: Fusion Strategies and Template Security, Phd Thesis, Michigan State University, Department of Computer Science and Engineering, 2008.
  13. E. L. Lehmann and J. P. Romano, Testing Statistical Hypotheses, Springer, 2005.
  14. M. A. T. Figueiredo and A. K. Jain, “Unsupervised learning of finite mixture models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 3, pp. 381–396, 2002. View at Publisher · View at Google Scholar · View at Scopus
  15. F. Zernike, Physica, 1934.
  16. L. B. Tran and T. H. Le, “Using wavelet-based contourlet transform illumination normalization for face recognition,” International Journal Modern Education and Computer Science, vol. 7, no. 1, pp. 16–22, 2015. View at Google Scholar
  17. A. K. Jain, S. Prabhakar, L. Hong, and S. Pankanti, “Filterbank-based fingerprint matching,” IEEE Transactions on Image Processing, vol. 9, no. 5, pp. 846–859, 2000. View at Publisher · View at Google Scholar · View at Scopus
  18. J. Haddadnia, K. Faez, and M. Ahmadi, “An efficient human face recognition system using Pseudo Zernike Moment Invariant and radial basis function neural network,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 17, no. 1, pp. 41–62, 2003. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Haddadnia and K. Faez, “Human face recognition based on shape information and pseudo zernike moment,” 5th Int. Fall Workshop Vision, Modeling and Visualization, pp. 113–118, 2000. View at Google Scholar
  20. J. Haddadnia, M. Ahmadi, and K. Faez, “An efficient method for recognition of human faces using higher orders Pseudo Zernike Moment Invariant,” in Proceedings of the 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002, pp. 330–335, May 2002. View at Publisher · View at Google Scholar · View at Scopus
  21. R. Raghavendra, A. Rao, and G. Hemantha Kumar, “A novel three stage process for palmprint verification,” in Proceedings of the International Conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2009, pp. 88–92, India, December 2009. View at Publisher · View at Google Scholar · View at Scopus
  22. G. Amayeh, G. Bebis, and M. Hussain, “A comparative study of hand recognition systems,” in Proceedings of the 1st International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics, ETCHB 2010, Istanbul, Turkey, August 2010. View at Publisher · View at Google Scholar · View at Scopus
  23. FVC (2004). Finger print verification contest 2004. http://bias.csr.unibo.it/fvc2004/download.asp.
  24. ORL, 1992. The ORL face database at the AT and T (Olivetti) Research Laboratory, http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html.
  25. The PolyU palmprint database. http://www.comp.polyu.edu.hk/biometrics.
  26. IIT Delhi Touchless Palmprint Database, http://www4.comp.polyu.edu.hk/~csajaykr/IITD/Database_Palm.htm.
  27. S. M. Lajevardi and Z. M. Hussain, “Higher order orthogonal moments for invariant facial expression recognition,” Digital Signal Processing, vol. 20, no. 6, pp. 1771–1779, 2010. View at Publisher · View at Google Scholar · View at Scopus
  28. A. Q. Hasan, R. R. Abdul, and S. Al-Haddad, “Fingerprint recognition using zernike moments,” The International Arab Journal of Information Technology, vol. 4, no. 4, pp. 372–376, 2007. View at Google Scholar
  29. S. Karar and R. Parekh, “Palm print recognition using zernike moments,” International Journal of Computer Applications, vol. 55, no. 16, pp. 15–19, 2012. View at Publisher · View at Google Scholar
  30. R. Mukundan, S. H. Ong, and P. A. Lee, “Image analysis by Tchebichef moments,” IEEE Transactions on Image Processing, vol. 10, no. 9, pp. 1357–1364, 2001. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  31. P.-T. Yap, R. Paramesran, and S.-H. Ong, “Image analysis by Krawtchouk moments,” IEEE Transactions on Image Processing, vol. 12, no. 11, pp. 1367–1377, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus