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

Youssef Elmir, Zakaria Elberrichi and Réda Adjoudj
Volume: 10, No: 4, Page: 555 ~ 567, Year: 2014
10.3745/JIPS.02.0007
Keywords: Hierarchical Fusion, LDA, Multimodal Biometric Fusion, PCA
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Abstract
Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

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Cite this article
IEEE Style
Youssef Elmir, Zakaria Elberrichi, and Réda Adjoudj, "Multimodal Biometric Using a Hierarchical Fusion of a Person’s Face, Voice, and Online Signature," Journal of Information Processing Systems, vol. 10, no. 4, pp. 555~567, 2014. DOI: 10.3745/JIPS.02.0007.

ACM Style
Youssef Elmir, Zakaria Elberrichi, and Réda Adjoudj, "Multimodal Biometric Using a Hierarchical Fusion of a Person’s Face, Voice, and Online Signature," Journal of Information Processing Systems, 10, 4, (2014), 555~567. DOI: 10.3745/JIPS.02.0007.