基于Gabor特征与投影字典对学习的人脸识别算法

J4 ›› 2016, Vol. 38 ›› Issue (03): 542-548.

基于Gabor特征与投影字典对学习的人脸识别算法

张建明1,2，刘阳春1,2，吴宏林1,2，李沛1,2

（1.长沙理工大学综合交通运输大数据智能处理湖南省重点实验室，湖南长沙 410114；
2.长沙理工大学计算机与通信工程学院，湖南长沙 410114）

收稿日期:2015-04-24 修回日期:2015-07-10 出版日期:2016-03-25 发布日期:2016-03-26
基金资助:
国家自然科学基金（61402053）；湖南省教育厅优秀青年项目（12B003）；湖南省交通厅科技计划（201334）；2015年湖南省研究生科研创新项目（CX2015B369）

A face recognition algorithm based on Gabor
feature and projective dictionary pair learning

ZHANG Jianming1,2，LIU Yangchun1,2，WU Honglin1,2，LI Pei1,2

（1.Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation,
Changsha University of Science and Technology,Changsha 410114；
2.School of Computer and Communication Engineering,
Changsha University of Science and Technology,Changsha 410114,China）

Received:2015-04-24 Revised:2015-07-10 Online:2016-03-25 Published:2016-03-26

摘要/Abstract

摘要：

为了提高人脸的识别率及其识别速度，提出了一种基于Gabor特征与投影字典对学习的人脸识别算法。由于Gabor特征对表情、光照和角度等变化具有较强的鲁棒性，首先提取人脸图像多方向多尺度的Gabor局部特征，并将经主成分分析降维后的增广Gabor特征作为训练数据，代替原始的训练样本。然后，根据训练数据同时学习综合字典与分析字典，综合字典具有重构能力，分析字典可以快速求出系数矩阵。最后，根据各类别的重构误差进行分类，以达到人脸识别的目的。在扩展的YaleB、ORL和AR人脸数据库上的实验结果表明，提出的算法不仅具有较高的识别率，而且能够有效地提高识别速度。

关键词: 人脸识别, Gabor特征, 综合字典, 分析字典

Abstract:

To improve the recognition rate and speed of face recognition, we propose a face recognition algorithm based on Gabor feature and projective dictionary pair learning. We first extract the Gabor features of the image at multiple scales and orientations, which shows significant robustness to the variations in expression, illumination and angle. The augmented Gabor features with reduced dimension are achieved through principle component analysis, which constructs a new training data to replace original training samples. Then a synthesis dictionary with reconstruction capability and an analysis dictionary with the capability of quickly obtaining representation coefficients are learned jointly during the training phase. The face is eventually identified by the reconstructed errors. Experimental results on the extended YaleB, ORL and AR database show that the proposed algorithm can get a high recognition rate and improve the recognition speed efficiently.

Key words: face recognition;gabor feature;synthesis dictionary;analysis dictionary

张建明1,2，刘阳春1,2，吴宏林1,2，李沛1,2. 基于Gabor特征与投影字典对学习的人脸识别算法[J]. J4, 2016, 38(03): 542-548.

ZHANG Jianming1,2，LIU Yangchun1,2，WU Honglin1,2，LI Pei1,2. A face recognition algorithm based on Gabor
feature and projective dictionary pair learning [J]. J4, 2016, 38(03): 542-548.

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