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Biometric systems based on a single source of information (unibiometric systems) suffer from limitations such as the lack of uniqueness and non-universality of the chosen biometric trait, noisy data and spoof attacks. In contrast, multibiometric systems fuse information from multiple biometric sources; an optimal combination of information can alleviate some of the limitations of unibiometric systems. Consequently, multibiometric systems achieve better performance compared to unibiometric systems and are being increasingly adopted in a number of applications. Some of the major issues in designing a multibiometric system are (i) determining the sources of biometric information to be fused, (ii) acquisition and processing sequence, (iii) type of information to be fused, (iv) optimal fusion methodology and (v) cost-benefit analysis. The goal of this project is to address these design issues systematically in order to maximize the performance of multibiometric systems.

S.C. Dass, K. Nandakumar and A.K. Jain, " A Principled Approach to Score Level Fusion in Multimodal Biometric Systems", Proc. of Audio- and Video-based Biometric Person Authentication (AVBPA) 2005, pp. 1049-1058, Rye Brook, NY, July 2005.

A.K. Jain, K. Nandakumar and A. Ross, " Score Normalization in Multimodal Biometric Systems", Pattern Recognition, Vol. 38, No. 12, pp. 2270-2285, December 2005.

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, March 2005.

A. K. Jain and A. Ross, " Multibiometric Systems", Communications of the ACM, Special Issue on Multimodal Interfaces , Vol. 47, No. 1, pp. 34-40, January 2004.
A. Ross and A.K. Jain, " Information Fusion in Biometrics", Pattern Recognition Letters, Vol. 24, Issue 13, pp. 2115-2125, September, 2003.


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