(2D)2 LDA:: An efficient approach for face recognition

被引：123

作者：

Noushath, S. ^{[1
]}

Kumar, G. Hemantha

Shivakumara, P.

机构：

[1] Univ Mysore, Dept Studies Comp Sci, Mysore 570006, Karnataka, India

[2] Natl Univ Singapore, Dept Comp Sci, Sch Comp, Singapore 117543, Singapore

来源：

PATTERN RECOGNITION | 2006年 / 39卷 / 07期

关键词：

principal component analysis; linear discriminant analysis; face recognition;

D O I：

10.1016/j.patcog.2006.01.018

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Although 2DLDA algorithm obtains higher recognition accuracy, a vital unresolved problem of 2DLDA is that it needs huge feature matrix for the task of face recognition. To overcome this problem, this paper presents an efficient approach for face image feature extraction, namely, (2D)(2)LDA method. Experimental results on ORL and Yale database show that the proposed method obtains good recognition accuracy despite having less number of coefficients. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：1396 / 1400

页数：5

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