Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (20): 245-248.

• 工程与应用 • Previous Articles    

Face recognition method using improved D-LDA based on DCT

ZHAO Chuan-qiang,WANG Hui-yuan   

  1. School of Information Science and Engineering,Shandong University,Ji’nan 250100,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-07-11 Published:2007-07-11
  • Contact: ZHAO Chuan-qiang



  1. 山东大学 信息科学与工程学院,济南 250100
  • 通讯作者: 赵传强

Abstract: D-LDA is a simple and efficient linear projection technique for feature extraction.But it may encounter two probloms in application:(1)it may indirectly misses some useful information in null space of Sw while deleting null space of Sb;(2)its optimization criteria is not directly related to the classification accuracy.Discrete Cosine Transform(DCT) can compress the information of original signal efficiently.We propose an approach based on DCT and improved D-LDA.We reduce the dimension first and then extract features by improved D-LDA on the low dimension space to overcome the shortcomings of D-LDA furthest.The experimental result will show that this method has a better performance.

Key words: Linear Discriminant Analysis(LDA), Discrete Cosine Transform(DCT), D-LDA, Small Sample Size problem(SSS)

摘要: D-LDA法是一种简单有效的线性特征提取方法,但在实际应用中往往存在以下两个问题:(1)去除Sb零空间的同时往往间接丢失了Sw零空间中的有用信息;(2)优化准则函数并不直接与识别率相关。离散余弦变换(DCT)能够有效地对原始图像的信息进行压缩,提出一种DCT与改进的D-LDA相结合的方法,首先利用DCT降维,然后在低维空间中应用一种改进的D-LDA方法进行特征提取,最大限度地克服D-LDA的不足。实验结果证明这种方法能获得较高的识别率。

关键词: 线性判别分析(LDA), 离散余弦变换(DCT), 直接LDA法(Direct LDA), 小样本问题(SSS)