首页|Multi-feature Multimodal Biometric Recognition Based on Quaternion Locality Preserving Projection

Multi-feature Multimodal Biometric Recognition Based on Quaternion Locality Preserving Projection

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This paper proposed Quaternion locality preserving projection (QLPP) for multi-feature multi-modal biometric recognition. Multi-features fill the real part or the three imaginary parts of quaternion to constitute the quaternion fusion features. In quaternion division ring, QLPP extracts the local information and finds essential manifold structure of the quaternion fusion features. Deferent from Quaternion principal component analysis (QPCA) and Quaternion fisher discriminant analysis (QFDA), QLPP takes advantage of the optimal linear approximations to find the nonlinear manifold structures. Two experiments are designed: one fuses four features from two biometric modalities, and the other fuses three features from three biometric modalities. The experimental results show the proposed algorithm achieves much better performance than the unimodal biometric algorithms, the traditional feature level fusion methods(weighted sum rule and series rule) and two quaternion representation methods(QPCA and QFDA).

Multimodal biometricsQuaternionFeature fusionQuaternion locality preserving projection (QLPP)

WANG Zhifang、ZHEN Jiaqi、LI Yanchao、LI Guoqiang、HAN Qi

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Department of Electronic Engineering, Heilongjiang University, Harbin 150008, China

Department of Information Security and Communication Technology, Norwegian University of Science and Technology, Gj?vik 2810, Norway

Department of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

This work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of China

615011766150505061601174

2019

10.1049/cje.2019.05.006

中国电子杂志(英文版)

中国电子杂志(英文版)

CSTPCDCSCDSCIEI
ISSN：1022-4653
年,卷(期)：2019.28(4)
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