摘要
线性判别分析（LDA）是人脸识别系统中用来降维的主要技术之一,但却受到小样本问题的限制,从而使其不能有效发挥其性能.本文通过把权值的概念引入LDA之中,使关联加权LDA方法有效地改善了小样本问题,但是它的分类效果却并不理想.为了解决这个问题,本文提出了基于Haar小波的关联加权LDA方法,该方法在Haar小波子带基础上,应用关联加权LDA方法,既解决了小样本问题,又改善了分类的效果.利用ORL及FERET两大人脸数据库进行了实验,其结果表明与最先进的几种方法相比较,HWRW-LDA方法具有更好的识别性能.
As is known to all of us,linear discriminative analysis （LDA） is one of the principal techniques used in face recognition systems.It can be worked on the whole face image,but LDA is limited by Small Sample Size problem.Related weighting LDA （RW-LDA） addresses the SSS problem by using conception of weighting,however,the classification of RW-LDA is not well.To address this problem,Related Weighting LDA based on Haar Wavelet （HWRW-LDA） which applying the RW-LDA on Haar wavelet subband is proposed in this paper.It improved classification performance as well as addressing the SSS problem.Experiments on ORL and FERET face database clearly demonstrate this and the graphical comparison of the algorithms clearly show that proposed method gets the better recognition performance comparing with the latest approaches.
出处
《华中师范大学学报（自然科学版）》
CAS
北大核心
2014年第1期33-36,45,共5页
Journal of Central China Normal University：Natural Sciences
基金
河南省教育厅科学技术研究重点项目（13A520367）.
