Exploiting global and local decisions for multimodal biometrics verification

Kar Ann Toh, Xudong Jiang, Wei Yun Yau

Research output: Contribution to journalArticlepeer-review

90 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)3059-3072
Number of pages14
JournalIEEE Transactions on Signal Processing
Issue number10
Publication statusPublished - 2004 Oct

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering


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