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Research Avenues in Multimodal Biometrics

Published on None 2010 by G Hemantha Kumar, Mohammad Imran
Recent Trends in Image Processing and Pattern Recognition
Foundation of Computer Science USA
RTIPPR - Number 1
None 2010
Authors: G Hemantha Kumar, Mohammad Imran
8ff26849-f3de-42b6-b324-37ef425bafc3

G Hemantha Kumar, Mohammad Imran . Research Avenues in Multimodal Biometrics. Recent Trends in Image Processing and Pattern Recognition. RTIPPR, 1 (None 2010), 1-8.

@article{
author = { G Hemantha Kumar, Mohammad Imran },
title = { Research Avenues in Multimodal Biometrics },
journal = { Recent Trends in Image Processing and Pattern Recognition },
issue_date = { None 2010 },
volume = { RTIPPR },
number = { 1 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 1-8 },
numpages = 8,
url = { /specialissues/rtippr/number1/969-92/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Recent Trends in Image Processing and Pattern Recognition
%A G Hemantha Kumar
%A Mohammad Imran
%T Research Avenues in Multimodal Biometrics
%J Recent Trends in Image Processing and Pattern Recognition
%@ 0975-8887
%V RTIPPR
%N 1
%P 1-8
%D 2010
%I International Journal of Computer Applications
Abstract

Growing concern the world over, related to personal and property safety has propelled rapid growth of security and surveillance related technologies. The biometric system is one such that can provide accurate and reliable scheme for person verification. The main aim of biometric based security system is to make sure that rendered service is accessed only by valid user. Biometric systems are of two types: unimodal and multimodal. In these multimodal biometric systems are gaining more popularity as it is capable of addressing some of the challenges involved in designing a biometric systems such as: non-universality, noise in sensed data, large intra-user variations and susceptibility to spoof attacks. In this paper, we give a brief overview of multimodal biometrics and its advantages, challenges, drawbacks and limitations. We also discuss the performance evaluation of multimodal biometrics for two and three modalities for different combinations of algorithms.

References
  1. A.Ross, K.Nandakumar, and A.K. Jain, Handbook of Multibiometrics, Springer-Verlag edition, 2006.
  2. J.Heo, S.Kong, B.Abidi, and M.Abidi, “Fusion of visible and thermal signatures with eyeglass removal forrobust face recognition,” in IEEE workshop on Object Tracking and Classification Beyond the visible spectrum in conjunction with (CVPR-2004), Washington, DC, USA, 2004, pp. 94–99.
  3. R.Singh, M.Vatsa, and A.Noore, “Integrated multilevel image fusion and match score fusion of visible and infrared face images for robust face recognition,” Pattern Recognition, vol. 41, pp. 880–893, 2008.
  4. S.Singh, A.Gyaourova, G.Bebis, and I.Pavlidies, “Infrared and visible image fusion for face recognition,” in of SPIE Defense and security symposium, 2004, pp. 585–596.
  5. D.R. Kisku, J. K. Singh, M. Tistarelli, and P.Gupta, “Multisensor biometric evidence fusion for person authentication using wavelet decomposition and monotonic decreasing graph,” in Proceedings of 7th International Conference on Adavnaces in Pattern Recognition (ICAPR-2009), Kolkata, India, 2009, pp. 205– 208.
  6. Y.Yao, X. Jing, and H. Wong, “Face and palmprint feature level fusion for single sample biometric recognition”, Nerocomputing, vol. 70, no. 7-9, pp. 1582–1586, 2007.
  7. X.Y. Jing, Y.F. Yao, J.Y. Yang, M. Li, and D. Zhang, “Face and palmprint pixel level fusion and kernel DCVRBF classifier for small sample biometric recognition,” Pattern Recognition, vol. 40, no. 3, pp. 3209–3224, 2007.
  8. P.Xiuqin, X.Xiaona, L.Yong, and C.Youngcun, “Feature fusion of multimodal recognition based on ear and profile face,” in proceedings SPIE-2008, 2008.
  9. A.Rattani and M.Tistarelli, “Robust multimodal and multiunit feature level fusion of face and iris biometrics,” in International Conference of Biometrics, Springer, 2009, pp. 960–969.
  10. G. Feng, K. Dong, D. Hu, and D. Zhang, “When faces are combined with palmprints:a novel biometric fusion strategy,” in First International Conference on Biometric Authentication (ICBA), 2004, pp. 701–707.
  11. X.Zhou and B.Bhanu, “Feature fusion of face and gait for human recognition at a distance in video,” in International Conference Pattern Recognition (ICPR-2006), Hong Kong, China, 2006, pp. 529–532.
  12. A. Ross and R.Govindarajan, “Feature level fusion using hand and face biometrics,” in Proceedings of SPIE Conference on Biometric Technology for Human Identification, 2004, pp. 196–204.
  13. J. Kittler, M. Hatef, R.P.W. Duin, and J. Matas, “On combining classifiers,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, pp. 226– 239, 1998.
  14. R.Snelick, U.Uludag, A.Mink, M.Indovina, and A.K. Jain, “Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 450 – 455, 2005.
  15. Y. Wang, T. Tan, and A. K. Jain, “Combining Face and Iris Biometrics for Identity Verification,” in proceedings of 4th International Conference on Audio and Video based Biometric Person Authentication (AVBPA, Guildford, UK), 2003, pp. 805– 813.
  16. R. Brunelli and D. Falavigna, “Person identification using multiple cues,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, pp. 955–965, 1995.
  17. V.Chatzis, A.G. Bors, and I.Pits, “Multimodal decisionlevel fusion for person authentication,” IEEE Transactions on systems, Man, and Cybernetics, Part A: Systems and Humans, vol. 29, no. 6, pp. 674–681, 1999.
  18. S. Ben-Yacoub, Y. Abdeljaoued, and E. Mayoraz, “Fusion of face and speech data for person identity verification,” IEEE Transactions on Neural Networks, vol. 10,pp. 1065–1074, 1999.
  19. A. Ross and A.K. Jain, “Information fusion in biometrics,” Pattern Recognition Letters, vol. 24, no. 13, pp. 2115–2125, 2003.
  20. A.K. Jain, L. Hong, and Y. Kulkarni, “A multimodal biometric system using fingerprint, face, and speech,” in International Conference on audio and Video based Biometric person authentication, Washington D.C., USA, 1999, pp. 182–187.
  21. S.Prabhakar and A.K. Jain, “Decision level fusion in fingerprint verification,” Pattern Recognition, vol. 35, no. 4, pp. 861–874, 2002.
  22. S. C. Dass, K. Nandakumar, and A.K. Jain, “A Principled Approach to Score Level Fusion in Multimodal Biometric Systems,” in proceedings of Audio and Video based Biometric person AuthenticationAVBPA- 2005, New York, USA, 2005, pp. 1049–1055.
  23. K. Nandakumar, Y. Chen, S. C. Dass, and A. K. Jain, “Likelihood ratio-based biometric score fusion,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 2, pp. 342 – 347, 2008.
  24. J.Daughman, “Combining multiple biometric,” Avaliable online at www.cl.ca.ac.uk/users/igd1000/combine.html, 2002.
  25. L.Lan and C.Y Suen, “Application of majority voting to pattern recognition,” IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, vol. 27, no. 5, pp. 553–568, 1997.
  26. L.L Kunchava, Combining pattern classifier-Methods and algorithm, Wiley edition, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Image Processing Biometrics Security