Face recognition based on adaptive weight and local singular value decomposition

doi:10.3778/j.issn.1002-8331.2009.14.053

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (14): 173-175.DOI: 10.3778/j.issn.1002-8331.2009.14.053

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

Face recognition based on adaptive weight and local singular value decomposition

LIU Min¹,LI Xiao-dong²,WANG Zhen-hai¹

1.School of Information，Linyi Normal University，Linyi，Shandong 276000，China
2.Key Lab. of Measurement and Control of Complex Sys. of Eng.，School of Automation，Southeast University，Nanjing 210096，China

Received:2008-12-12 Revised:2009-03-02 Online:2009-05-11 Published:2009-05-11
Contact: LIU Min

融合自适应加权和局部奇异值分解的人脸识别

刘敏¹,李晓东²,王振海¹

1.临沂师范学院信息学院，山东临沂 276000
2.东南大学自动化学院复杂工程系统测量与控制教育部重点实验室，南京 210096

通讯作者: 刘敏

Abstract

Abstract: A face recognition method based on adaptive weight and local singular value decomposition is proposed in this paper.Firstly，each facial image in the training sample set is divided into five special regions，and singular value decomposition is performed on these regions.Some bigger singular values are taken to form the feature vector of each region，subsequently.Secondly，the same approach as what has given above is used to get the feature vectors of all regions in the testing facial image.Weight value that belongs to each local part is calculated based on the within-class average distance and the class average distance corresponding to each local area.Finally，the membership degrees of each region in the testing facial image to corresponding regions of all training facial images are computed，and the recognition result can be obtained using weighted fusion scheme.The experiment results based on ORL and FERET face database show that the method is efficient and feasible.

Key words: face recognition, Singular Value Decomposition（SVD）, adaptive weight

摘要： 提出了融合自适应加权和局部奇异值分解的人脸识别方法。首先，对每个训练样本分割出人脸图像的5个特殊区域并分别进行奇异值分解，提取一些较大的奇异值构成每一区域的特征向量。然后，计算各局部块的类内距离平均值和类间距离平均值，从而得到各部分对应的权值。识别阶段，计算待识别人脸图像每一区域对所有训练样本人脸图像相应区域的隶属度，最后采用加权融合策略做出判断。基于ORL和FERET人脸数据库的实验结果表明提出的方法具有有效性和可行性。

关键词: 人脸识别, 奇异值分解, 自适应加权

LIU Min¹,LI Xiao-dong²,WANG Zhen-hai¹. Face recognition based on adaptive weight and local singular value decomposition[J]. Computer Engineering and Applications, 2009, 45(14): 173-175.

刘敏¹,李晓东²,王振海¹. 融合自适应加权和局部奇异值分解的人脸识别[J]. 计算机工程与应用, 2009, 45(14): 173-175.

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Face recognition based on adaptive weight and local singular value decomposition

融合自适应加权和局部奇异值分解的人脸识别

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