Large-Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Biometric Verification: Looking Beyond Raw Similarity Scores
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
A new cohort normalization using local acoustic information for speaker verification
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Qualitative fusion of normalised scores in multimodal biometrics
Pattern Recognition Letters
Score normalization in multimodal biometric systems
Pattern Recognition
Handbook of Multibiometrics
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The effectiveness of a multibiometric system can be improved by modifying the scores obtained from the degraded modalities in an appropriate manner. Score normalization is a promising method to improve the system performance. In this paper, we propose a new method entitled as multi-normalization based fusion, to improve the robustness and efficiency of a multibiometric system, under various noise conditions. As the match score values from the individual matchers follow nonhomogeneous statistical distributions. we propose different score normalization techniques for the complementary modalities employed. The performance of the proposed technique is analysed in the context of fingerprint and voice biometrics using sum rule of fusion. Experimental results show that this fusion strategy performs considerably better, than the baseline systems. The biometric solution that we provided could be easily integrated with any multibiometric system with score level fusion.