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



  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:


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



关键词: Gabor, 相关系数, 近邻样本, 协作表示, 人脸识别


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


  • TP391.4