A Novel Framework for Multimodal Biometrics based on Dimensionality Reduction Technique for Reducing Overlapping Features

In this article, the effect of dimensionality reduction in the authentication process while recognizing the multiple traits is projected. In this paper, the templates of speech face and finger print are fused in serial fusion mode. The concepts Generalized Gamma Distribution (GGD) is considered for modeling the facial data. The performance of the model is evaluated using synthetic data and evaluation is carried out by considering metrics like False Acceptance Rate (FAR), Acceptance Rate, and False Rejection Rate (FRR).

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