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Multimodal Biometric Using a Hierarchical Fusion of a Person’s Face, Voice, and Online Signature

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초록

Biometric performance improvement is a challenging task. In this paper, ahierarchical strategy fusion based on multimodal biometric system is presented. Thisstrategy relies on a combination of several biometric traits using a multi-level biometricfusion hierarchy. The multi-level biometric fusion includes a pre-classification fusionwith optimal feature selection and a post-classification fusion that is based on thesimilarity of the maximum of matching scores. The proposed solution enhancesbiometric recognition performances based on suitable feature selection and reduction,such as principal component analysis (PCA) and linear discriminant analysis (LDA), asmuch as not all of the feature vectors components support the performanceimprovement degree.

Abstract

Biometric performance improvement is a challenging task. In this paper, ahierarchical strategy fusion based on multimodal biometric system is presented. Thisstrategy relies on a combination of several biometric traits using a multi-level biometricfusion hierarchy. The multi-level biometric fusion includes a pre-classification fusionwith optimal feature selection and a post-classification fusion that is based on thesimilarity of the maximum of matching scores. The proposed solution enhancesbiometric recognition performances based on suitable feature selection and reduction,such as principal component analysis (PCA) and linear discriminant analysis (LDA), asmuch as not all of the feature vectors components support the performanceimprovement degree.

참고문헌 (27)

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