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


Youssef Elmir, Zakaria Elberrichi, Réda Adjoudj, Journal of Information Processing Systems Vol. 10, No. 4, pp. 555-567, Dec. 2014  

https://doi.org/10.3745/JIPS.02.0007
Keywords: Hierarchical Fusion, LDA, Multimodal Biometric Fusion, PCA
Fulltext:

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
[APA Style]
Elmir, Y., Elberrichi, Z., & Adjoudj, R. (2014). Multimodal Biometric Using a Hierarchical Fusion of a Person’s Face, Voice, and Online Signature. Journal of Information Processing Systems, 10(4), 555-567. DOI: 10.3745/JIPS.02.0007.

[IEEE Style]
Y. Elmir, Z. Elberrichi, R. 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. 2014. 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.