Face recognition based on illumination normalization and block-based completed local binary pattern

Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (11): 145-149.

Previous Articles Next Articles

Face recognition based on illumination normalization and block-based completed local binary pattern

ZHOU Wei1, CHENG Yong2, CAO Xuehong1，2

1.College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2.School of Communication Engineering, Nanjing Institute of Technology, Nanjing 211167, China

Online:2015-06-01 Published:2015-06-12

基于光照归一化分块完备LBP特征的人脸识别

周巍1，程勇2，曹雪虹1，2

1.南京邮电大学通信与信息工程学院，南京 210003
2.南京工程学院通信工程学院，南京 211167

Abstract

Abstract: Aiming at the problem of face recognition under complex illumination, an effective face recognition method based on illumination normalization and block-based completed local binary pattern is proposed. The method performs illumination normalization on face images, then extracts the B-CLBP features from the processed face images in order to form the B-CLBP histogram, applies the nearest neighbor principle for face recognition. The experimental results on Extended Yale B face databases demonstrate that the proposed method can achieve significant recognition rate under complex illumination conditions.

Key words: face recognition, illumination normalization, Block-based Completed Local Binary Pattern（B-CLBP）

摘要： 针对复杂光照条件下的人脸识别，提出了一种基于光照归一化分块完备局部二值模式（B-CLBP）特征的人脸识别算法。该方法对人脸图像进行光照归一化预处理，对处理后的人脸图像进行B-CLBP特征提取，融合成B-CLBP直方图，根据最近邻准则进行分类识别。在Extended Yale B人脸库上的实验结果表明，所提算法可以有效提高复杂光照条件下的人脸识别率。

关键词: 人脸识别, 光照归一化, 分块完备局部二值模式

ZHOU Wei1, CHENG Yong2, CAO Xuehong1，2. Face recognition based on illumination normalization and block-based completed local binary pattern[J]. Computer Engineering and Applications, 2015, 51(11): 145-149.

周巍1，程勇2，曹雪虹1，2. 基于光照归一化分块完备LBP特征的人脸识别[J]. 计算机工程与应用, 2015, 51(11): 145-149.

[1]	QIAO Hui, ZHOU Shuisheng. Nolinear Angle 2DPCA and Its Application on Face Recognition [J]. Computer Engineering and Applications, 2021, 57(8): 112-118.
[2]	HU Wentao, CHEN Xiuhong. Low-Rank Projection Learning Based on Neighbor Graph [J]. Computer Engineering and Applications, 2021, 57(7): 209-214.
[3]	WANG Peng, YE Xueyi, WANG Tao, QIAN Dingwei. Face Recognition Based on Double Variation and Double Space Local Directional Pattern [J]. Computer Engineering and Applications, 2021, 57(4): 91-99.
[4]	SHI Zhengyu, CHEN Renwen, HUANG Bin. Low-Resolution Face Recognition Based on Self-Normalizing Neural Network [J]. Computer Engineering and Applications, 2021, 57(3): 137-143.
[5]	LI Junyao, LI Zhihui, XIE Lanchi, HOU Xinyu, YE Dong. Advances of Age Progression Based Cross-Age Face Recognition [J]. Computer Engineering and Applications, 2021, 57(24): 27-38.
[6]	LIU Jinjin, LI Qingbao, LI Xiaonan. Neural Network Compression Algorithm Based on Adversarial Learning and Knowledge Distillation [J]. Computer Engineering and Applications, 2021, 57(21): 180-187.
[7]	XU Xialing, LIU Tao, TIAN Guohui, YU Wenjuan, XIAO Dajun, LIANG Shanpeng. Review of Occlusion Face Recognition Methods [J]. Computer Engineering and Applications, 2021, 57(17): 46-60.
[8]	XU Ranran, WU Xiaojun, YIN Hefeng. Face Recognition via Discriminative Non-negative Representation Based Classification [J]. Computer Engineering and Applications, 2021, 57(13): 147-153.
[9]	WANG Yu, LIU Fan, WANG Fei. Autoencoder Based Sparse Representation for Single Sample Face Recognition [J]. Computer Engineering and Applications, 2021, 57(1): 168-172.
[10]	DONG Yanhua, ZHANG Shumei, ZHAO Junli. Review of Occlusion Face Recognition Method [J]. Computer Engineering and Applications, 2020, 56(9): 1-12.
[11]	LIN Kezheng, ZHANG Yuanming, LI Haotian. Research on HOG Feature Extraction Algorithm Weighted by Information Entropy [J]. Computer Engineering and Applications, 2020, 56(6): 147-152.
[12]	YUAN Xiaoping, CUI Qiwen, CHENG Gan, ZHANG Xia, ZHANG Yi, WANG Suyuan. Improved Gabor Self Quotient Image Algorithm and Its Application to Face Recognition [J]. Computer Engineering and Applications, 2020, 56(5): 206-213.
[13]	ZHANG Feixiang, YU Xueru, HE Weifeng, LI Chen. Face Recognition with Improved Loss Function and Multiple-Norm [J]. Computer Engineering and Applications, 2020, 56(24): 144-150.
[14]	CHEN Zhe, WU Xiaojun. Robust Face Recognition Algorithm Based on Structured Low-Rank Recovery [J]. Computer Engineering and Applications, 2019, 55(6): 126-132.
[15]	BAI Chuang, CHEN Xiang. Research on New LeNet-FC Convolutional Neural Network Model Algorithm [J]. Computer Engineering and Applications, 2019, 55(5): 105-111.

Face recognition based on illumination normalization and block-based completed local binary pattern

基于光照归一化分块完备LBP特征的人脸识别

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics