# [1]李邺,等.一种结合稀疏表示和切比雪夫矩的人脸识别算法[J].东南大学学报(自然科学版),2012,42(2):249-253.[doi:10.3969/j.issn.1001-0505.2012.02.011] 　Li Ye,Chen Beijing,et al.Face recognition algorithm by using sparse representation and Tchebichef moments[J].Journal of Southeast University (Natural Science Edition),2012,42(2):249-253.[doi:10.3969/j.issn.1001-0505.2012.02.011] 点击复制 一种结合稀疏表示和切比雪夫矩的人脸识别算法() 分享到： var jiathis_config = { data_track_clickback: true };

42

2012年第2期

249-253

2012-03-20

## 文章信息/Info

Title:
Face recognition algorithm by using sparse representation and Tchebichef moments

1 东南大学生物科学与医学工程学院,南京 210096; 2 东南大学影像科学与技术实验室,南京 210096; 3 南京信息工程大学计算机与软件学院,南京 210044
Author(s):
1 School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
2 Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China
3 School of Computer and

Keywords:

TP391.4
DOI:
10.3969/j.issn.1001-0505.2012.02.011

Abstract:
Based on the sparse representation-based classification(SRC)algorithm, taking the advantages of Tchebichef moments in image representation and noise robustness, a face recognition algorithm combining the sparse representation and Tchebichef moments is proposed to recognize the face images with and without additive noise. The mathematical derivation and the specific procedure of the algorithm are given, and the experiments are made to verify the algorithm. The experimental results obtained from the extended Yale B database and the AR database show that when the feature space dimension is 496, the recognition rate of the proposed algorithm is 98.33% and 88.72% under various lighting conditions and expressions, respectively. When the proportion of pixels damaged by salt-pepper noise is less than 60%, the recognition rate is 100%. In terms of the robustness against various image details, this algorithm outperforms the nearest neighbor method, the nearest subspace method and the conventional SRC algorithm all of which are based on the randomfaces.

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