计算机工程与科学2011，Vol.33Issue(7)：89-93,5.DOI:10.3969/j.issn.1007-130X.2011.07.017
一种改进的线性判别分析算法在人脸识别中的应用
An Improved LDA Algorithm and Its Application to Face Recognition
刘忠宝1
作者信息
- 1. 江南大学信息工程学院,江苏无锡214122;山西大学商务学院信息学院,山西太原030031
- 折叠
摘要
Abstract
Linear discriminant analysis (LDA) is a typical feature extraction method, but there exist at least two critical drawbacks in LDA: the small sample size problem and the rank limitation problem. In order to solve the above problems, this paper presents an improved LDA method (ILDA) which redefines the between-class scatter matrix and the within-class scatter matrix. ILDA can effectively extract the discriminative information included in the null subspace and the non-null subspace of a within-class scatter matrix. Numerical experiments on some facial databases show ILDA achieves good performance of face recognition.关键词
线性判别分析/类内离散度矩阵/类间离散度矩阵/人脸识别Key words
linear discriminant analysis(LDA)/within-class scatter matrix/between-class scatter matrix/face recognition分类
信息技术与安全科学引用本文复制引用
刘忠宝..一种改进的线性判别分析算法在人脸识别中的应用[J].计算机工程与科学,2011,33(7):89-93,5.
