Multimodal biometric fusion at feature level: Face and palmprint

M. I. Ahmad, W. L. Woo, S. S. Dlay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010
PublisherIEEE
Pages801-805
Number of pages5
ISBN (Electronic)9781861353696
ISBN (Print)9781424488582
Publication statusPublished - 20 Sep 2010
Event2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010 - Newcastle upon Tyne, United Kingdom
Duration: 21 Jul 201023 Jul 2010

Conference

Conference2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010
CountryUnited Kingdom
CityNewcastle upon Tyne
Period21/07/1023/07/10

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