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Optical Engineering

Bimodal biometrics based on a representation and recognition approach
Author(s): Yong Xu; Aini Zhong; Jian Yang; David Zhang
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Paper Abstract

It has been demonstrated that multibiometrics can produce higher accuracy than single biometrics. This is mainly because the use of multiple biometric traits of the subject enables more information to be used for identification or verification. In this paper, we focus on bimodal biometrics and propose a novel representation and recognition approach to bimodal biometrics. This approach first denotes the biometric trait sample by a complex vector. Then, it represents the test sample through the training samples and classifies the test sample as follows: let the test sample be expressed as a linear combination of all the training samples each being a complex vector. The proposed approach obtains the solution by solving a linear system. After evaluating the effect, in representing the test sample of each class, the approach classifies the test sample into the class that makes the greatest effect. The approach proposed is not only novel but also simple and computationally efficient. A large number of experiments show that our method can obtain promising results.

Paper Details

Date Published: 1 March 2011
PDF: 8 pages
Opt. Eng. 50(3) 037202 doi: 10.1117/1.3554740
Published in: Optical Engineering Volume 50, Issue 3
Show Author Affiliations
Yong Xu, Harbin Institute of Technology (China)
Aini Zhong, Harbin Institute of Technology (China)
Jian Yang, Nanjing Univ. of Science & Technology (China)
David Zhang, The Hong Kong Polytechnic Univ. (Hong Kong, China)

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