Abstract
Multimodal biometric systems have proven advantages over single biometric systems as they are using multiple traits of users. The intra-class variance provided by using more than one trait results in a high identification rate. Still, one of the missing parts in a multimodal system is inattention to the discriminability of each rank list for each specific user. This paper introduces a novel approach to select a combination of rank lists in rank level so that it provides the highest discrimination for any specific query. The rank list selection is based on pseudo-scores lists that are created by combination of rank lists and resemblance probability distribution of users. The experimental results on a multimodal biometric system based on frontal face, profile face, and ear indicated higher identification rate by using novel confidence based rank level fusion.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ross, A.A., Nandakumar, K., Jain, A.K.: Handbook of multibiometrics. Springer Science & Business Media (2006)
Jain, A.K., Flynn, P., Ross, A.A.: Handbook of biometrics. Springer Science & Business Media (2007)
Revett, K.: Behavioral biometrics: a remote access approach. John Wiley & Sons (2008)
Prabhakar, S., Jain, A.K.: Decision-level fusion in fingerprint verification. Pattern Recognition 35(4), 861–874 (2002)
Mowar, M., Gavrilova, M.L.: Multimodal biometric system using rank-level fusion approach. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 39(4), 867–878 (2009)
Bhatnagar, J., Kumar, A., Saggar, N.: A novel approach to improve biometric recognition using rank level fusion. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp 1–6. IEEE (2007)
Kumar, A., Shekhar, S.: Personal identification using multibiometrics rank-level fusion. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews. 41(5), 743–752 (2011)
Lee, Y.-J., Lee, K.-H., Jee, H., Gil, Y.H., Choi, W., Ahn, D., Pan, S.B.: Fusion for multimodal biometric identification. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 1071–1079. Springer, Heidelberg (2005)
Monwar, M.M., Gavrilova, M., Wang, Y.: A novel fuzzy multimodal information fusion technology for human biometric traits identification. In: 2011 10th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI* CC), pp. 112–119. IEEE (2011)
Marasco, E., Abaza, A., Cukic, B.: Why rank-level fusion? and what is the impact of image quality?
Abaza, A., Ross, A.: Quality based rank-level fusion in multibiometric systems. In: IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems, BTAS 2009, pp. 1–6. IEEE (2009)
Alam, M.R., Bennamoun, M., Togneri, R., Sohel, F.: Confidence-based rank-level fusion for audio-visual person identification system. In: 3rd International Conference on Pattern Recognition Applications and Methods, 2014, pp. 608–615 (2014)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.: Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 711–720 (1997)
Talebi, H., Gavrilova, M.: Prior resemblance probability of users for multimodal biometrics rank fusion. In: IEEE International Conference on Identity, Security and Behavior Analysis (ISBA 2015). IEEE (2015)
Monwar, M., Gavrilova, M.: Fes: a system for combining face, ear and signature biometrics using rank level fusion. In: Fifth International Conference on Information Technology: New Generations, 2008, pp. 922–927. IEEE (2008)
Bhattacharyya, A.: On a measure of divergence between two multinomial populations. Sankhyā: The Indian Journal of Statistics, 401–406 (1946)
Phillips, P.J., Wechsler, H., Huang, J., Rauss, P.J.: The feret database and evaluation procedure for face-recognition algorithms. Image and Vision Computing 16(5), 295–306 (1998)
USTB ear database, china. http://www.ustb.edu.cn/resb/ (accessed May 11, 2008)
Cover, T., Hart, P.: Nearest neighbor pattern classification. IEEE Transactions on Information Theory 13(1), 21–27 (1967)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Talebi, H., Gavrilova, M.L. (2015). Confidence Based Rank Level Fusion for Multimodal Biometric Systems. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-23192-1_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23191-4
Online ISBN: 978-3-319-23192-1
eBook Packages: Computer ScienceComputer Science (R0)