Two-dimensional FLD for face recognition

被引：167
|
作者：
Xiong, HL [1 ]
Swamy, MNS [1 ]
Ahmad, MO [1 ]
机构：
[1] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada
来源：
PATTERN RECOGNITION | 2005年 / 38卷 / 07期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Fisher criterion; principal component analysis (PCA); linear discriminant analysis (LDA);
D O I：
10.1016/j.patcog.2004.12.003
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a new scheme of face image feature extraction, namely, the two-dimensional Fisher linear discriminant. Experiments on the ORL and the UMIST face databases show that the new scheme outperforms the PCA and the conventional PICA + FLD schemes, not only in its computational efficiency, but also in its performance for the task of face recognition. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：1121 / 1124
页数：4
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