J4 ›› 2015, Vol. 42 ›› Issue (3): 115-121.doi: 10.3969/j.issn.1001-2400.2015.03.020

• 研究论文 • 上一篇    下一篇

近邻样本协作表示的人脸识别算法

魏冬梅1,2;周卫东1   

  1. (1. 山东师范大学 物理与电子科学学院,山东 济南  250014;
    2. 山东大学 信息科学与工程学院,山东 济南  250100)
  • 收稿日期:2014-02-19 出版日期:2015-06-20 发布日期:2015-07-27
  • 通讯作者: 魏冬梅
  • 作者简介:魏冬梅(1978-),女,讲师,山东大学博士研究生,E-mail:weidongmei2@163.com.
  • 基金资助:

    山东省高等学校科技计划资助项目(J14LN06)

Face recognition using collaborative representation with neighbors

WEI Dongmei1,2;ZHOU Weidong1   

  1. (1. College of Physics and Electronics, Shandong Normal Univ., Jinan  250014, China;
    2. School of Information Science and Engineering, Shandong Univ., Jinan  250100, China)
  • Received:2014-02-19 Online:2015-06-20 Published:2015-07-27
  • Contact: WEI Dongmei

摘要:

在Gabor特征空间,根据相关系数寻找测试图像的近邻样本,并用这些近邻样本构造完备的冗余字典,从而提出一种基于Gabor特征的近邻样本协作表示的人脸识别算法.在l2范数约束下,利用可变厚度的紧致字典对测试图像进行稀疏表示,根据稀疏系数逐类计算重构图像和测试图像之间的误差,并判断测试图像所属类别.该算法在FERET、ORL和AR数据上进行了无遮挡测试,在AR库上进行了有遮挡测试.实验结果表明,无论有无遮挡,识别速度和识别率都得到了明显改善.

关键词: Gabor, 相关系数, 近邻样本, 协作表示, 人脸识别

Abstract:

An improved face recognition algorithm using the collaborative representation with nearer neighbors of the testing image is proposed. As a measurement to find the neighboring testing sample,the correlation coefficient between the testing sample and training samples is calculated in the Gabor-feature space. Neighbors of the testing sample compose the compact over-completed dictionary which is variable for different testing samples. The testing image is represented collaboratively by the variable "thickness" compact dictionary and the sparse representation coefficient is calculated with l2 minimization. The error between the reconstructed image and the testing image categorizes the testing image. This proposed algorithm has been carried out in database of FERET, ORL and AR with variations of lighting, expression, pose, and occlusion. Extensive experiments demonstrate that the proposed approach is superior both in recognition rate and in speed.

Key words: Gabor, correlators, neighbors, collaborative representation, face recognition

中图分类号: 

  • TP391.4