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An enhanced thermal face recognition method based on multiscale complex fusion for Gabor coefficients

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Abstract

The recognition of thermal face is a very promising strategy in biometrics. It is invariant to illumination, robust to pose and immune to forgery. However, thermal face image consist of face heat energy and face counter information mainly, and it makes lower discrimination for inter-class. In this paper, an enhanced thermal face recognition approach based on Multiscale Complex Fusion for Gabor coefficients (MCFG) is proposed. Initially, the Complex Gabor Jet Descriptor (CGJD) is acquired based on the block mean and standard deviation generated from the magnitude, phase, real and imaginary parts of Gabor coefficients. Then, the Complex LDA (CLDA) algorithm and feature level fusion are implemented on multiscale Gabor coefficients to reduce the dimension and enhance the discrimination. Experiments conducted on two thermal face databases NVIE and IRIS, which have some challenging thermal face images, show that the proposed thermal face recognition approach significantly outperforms the state-of-the-art approaches.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Number: 61100187) and the Fundamental Research Funds for the Central Universities (Grant Number: HIT. NSRIF. 2010046, HIT. NSRIF. 2013061).

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Author notes

  1. Qiong Li

    Present address: Science Zone of Harbin Institute of Technology, Room 1523, Building 2A, No.2 Yikuang Street, Nangang District, Harbin, 150080, China

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150080, China

    Ning Wang, Qiong Li, Ahmed A. Abd El-Latif, Jialiang Peng & Xiamu Niu

  2. Mathematics Department, Faculty of Science, Menoufia University, Shebin El-Koom, 32511, Egypt

    Ahmed A. Abd El-Latif

  3. Information and Network Administration Center, Heilongjiang University, Harbin, 150080, China

    Jialiang Peng

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  1. Ning Wang
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  3. Ahmed A. Abd El-Latif
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Correspondence to Qiong Li.

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Wang, N., Li, Q., Abd El-Latif, A.A. et al. An enhanced thermal face recognition method based on multiscale complex fusion for Gabor coefficients. Multimed Tools Appl 72, 2339–2358 (2014). https://doi.org/10.1007/s11042-013-1551-4

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