Multimodal biometric fusion at feature level: Face and palmprint

Ahmad, Muhammad Imran, Woo, Wai Lok and Dlay, Satnam (2010) Multimodal biometric fusion at feature level: Face and palmprint. In: CSNDSP 2010 - 2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, 21st - 23rd July 2010, Newcastle upon Tyne, UK.

Full text not available from this repository.
Official URL:


Multimodal biometrics has recently attracted substantial interest for its high performance in biometric recognition system. In this paper we introduce multimodal biometrics for face and palmprint images using fusion techniques at the feature level. Gabor based image processing is utilized to extract discriminant features, while principal component analysis (PCA) and linear discriminant analysis (LDA) are used to reduce the dimension of each modality. The output features of LDA are serially combined and classified by a Euclidean distance classifier. The experimental results based on ORL face and Poly-U palmprint databases proved that this fusion technique is able to increase biometric recognition rates compared to that produced by single modal biometrics.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Face recognition, Multimodal biometrics, Palmprint recognition
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 14 May 2019 10:39
Last Modified: 10 Oct 2019 19:00

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics