Face Recognition Based on Rearranged Modular 2DPCA

被引：0
|
作者：
Huxidan [1 ,2 ]
Liu, Wanquan [2 ]
Lu, Chong [1 ]
机构：
[1] YiLi Normal Coll, Dept Comp Sci, Yining 835000, Peoples R China
[2] Curtin Univ, Dept Comp, Perth, WA, Australia
来源：
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE | 2012年 / 6839卷
关键词：
Face recognition; subspace method; rearranged modular 2DPCA; COMPONENT ANALYSIS; EIGENFACES;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we propose a. novel Rearranged Modular 2DPCA (Rm2DPCA) algorithm for face recognition. In the proposed algorithm; the original images are first divided into modular images. Then, the sub-images are rearranged to form a 2D matrix. A covariance matrix is constructed directly using all the arranged matrices, and its eigenvectors are derived for image feature extraction. Experiments compared with other similar approaches show that this method has two advantages: One is its better recognition performance, the other is less computational cost.
引用
收藏
页码：395 / +
页数：3
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