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A novel face recognition method based on IWLD and IWBC

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Abstract

This paper presents a face recognition method using improved Weber local descriptor (IWLD) and improved Weber binary coding method. Compared to the existing Weber local descriptor, the proposed IWLD represent local patterns more effectively and accurately by introducing novel Weber magnitude and orientation components. In order to extract more discriminative and robust feature for face recognition, the IWBC is proposed to encode the cues embedded in IWLD. Moreover, to reduce the dimension of feature extracted by IWBC and enhance its discriminative ability, the block-based Fishers linear discriminant (BFLD) is employed to learn a projection matrix from the training set. Experimental results on three (AR, FERET and PolyU-NIR) challenging databases demonstrate the effectiveness and robustness of our proposed method.

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Abbreviations

IWLD:

improved Weber local descriptor

WLD:

Weber local descriptor

IWBC:

improved Weber binary code

WBC:

Weber binary coding

FR:

face recognition

BFLD:

block-based Fishers linear discriminant

LSF:

local statistical feature

LBP:

local binary pattern

LBMP :

local binary magnitude pattern

LXOP :

local XOR (exclusive or) orientation pattern

LSF-based FR:

local statistical feature based face recognition

LXP:

local XOR (exclusive or) pattern

IDLS:

image decomposition method based on local structure

LDA:

linear discriminant analysis

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Acknowledgments

This work was supported by National Instrument Development Special Program of China under the grants 2013YQ03065101, 2013YQ03065105, Ministry of Science and Technology of China under National Basic Research Project under the grants 2010CB731803, and by National Natural Science Foundation of China under the grants 61221003, 61290322, 61174127, 61273181, 60934003, 61290322 and U1405251, the Program of New Century Talents in University of China under the grant NCET-13-0358, the Science and Technology Commission of Shanghai Municipal, China under the grant 13QA1401900, Postdoctoral Science Foundation of China under the grants 2014M551406.

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Authors and Affiliations

  1. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

    Bao-Qing Yang, Tao Zhang, Chao-Chen Gu, Kai-Jie Wu & Xin-Ping Guan

  2. Key Laboratory of System Controal and Information Processing, Ministry of Education of China, 800 Dongchuan Road, Shanghai, People’s Republic of China

    Bao-Qing Yang, Tao Zhang, Chao-Chen Gu, Kai-Jie Wu & Xin-Ping Guan

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  1. Bao-Qing Yang
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  2. Tao Zhang
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Correspondence to Chao-Chen Gu.

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Yang, BQ., Zhang, T., Gu, CC. et al. A novel face recognition method based on IWLD and IWBC. Multimed Tools Appl 75, 6979–7002 (2016). https://doi.org/10.1007/s11042-015-2623-4

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  • DOI: https://doi.org/10.1007/s11042-015-2623-4

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