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Exploiting global and local decisions for multimodal biometrics verification

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3 Author(s)
Kar-Ann Toh ; Inst. for Infocomm Res., Singapore, Singapore ; Xudong Jiang ; Wei-Yun Yau

In this paper, we address the multimodal biometric decision fusion problem. By exploring into the user-specific approach for learning and threshold setting, four possible paradigms for learning and decision making are investigated. Since each user requires a decision hyperplane specific to him in order to achieve good verification accuracy, those tedious iterative training methods like the neural network approach would not be suitable. We propose to use a model that requires only a single training step for this application. The four global and local learning and decision paradigms are then explored to observe their decision capability. Besides the proposal of a relevant receiver operating characteristic performance for the local decision, extensive experiments were conducted to observe the verification performance for fusion of two and three biometrics.

Published in:

Signal Processing, IEEE Transactions on  (Volume:52 ,  Issue: 10 )