Face recognition study based on Gabor-2DLDA method

doi:10.3778/j.issn.1002-8331.2008.35.053

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (35): 179-181.DOI: 10.3778/j.issn.1002-8331.2008.35.053

• 图形、图像、模式识别 • Previous Articles Next Articles

Face recognition study based on Gabor-2DLDA method

CHENG Wan-li,LI Wei-sheng

Institute of Computer Science and Technology，Chongqing University of Posts and Telecommunications，Chongqing 400065，China

Received:2008-06-12 Revised:2008-09-08 Online:2008-12-11 Published:2008-12-11
Contact: CHENG Wan-li

基于Gabor-2DLDA方法的人脸识别研究

程万里,李伟生

重庆邮电大学计算机科学与技术研究所，重庆 400065

通讯作者: 程万里

Abstract

Abstract: Combined with Gabor wavelet and Two-Dimensional LDA（2DLDA），a novel method for face recognition is presented.First，Gabor wavelet is used to transform the face images.Then 2DLDA is used to compress the feature.Finally，the nearest neighbor rule is used to classify.ORL and Yale face databases are used to test this new method.It shows that the recognition rate is higher than any other conditional method and the computational complexity did not increase significantly.

Key words: face recognition, Two-Dimensional LDA（2DLDA）, Gabor wavelet

摘要： 结合Gabor小波、二维线性鉴别分析（2DLDA）的特点，提出一种人脸识别方法。算法首先对人脸图像进行Gabor小波变换，然后进行2DLDA处理，最后使用最近邻法则进行分类。使用这种方法在ORL、Yale人脸库上进行测试，结果表明，Gabor-2DLDA方法比其它传统方法具有更优的性能，而且在提高识别率的同时算法的复杂程度并没有明显增加。

关键词: 人脸识别, 二维线性鉴别分析（2DLDA）, Gabor小波

CHENG Wan-li,LI Wei-sheng. Face recognition study based on Gabor-2DLDA method[J]. Computer Engineering and Applications, 2008, 44(35): 179-181.

程万里,李伟生. 基于Gabor-2DLDA方法的人脸识别研究[J]. 计算机工程与应用, 2008, 44(35): 179-181.

[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 study based on Gabor-2DLDA method

基于Gabor-2DLDA方法的人脸识别研究

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics