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基于加权小波变换和2D-PCA的人脸识别改进算法

Keywords: 人脸识别,加权小波变换,2D-PCA算法,最近邻分类器

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Abstract:

基于小波变换的人脸识别方法通常将图像变换成低频和高频信息,传统的人脸识别算法大多数都是基于小波变换后的低频信息,没有充分利用高频信息,造成了高频信息中对识别有利信息的丢失.本文提出了一种基于加权小波变换和2D-PCA的人脸识别改进算法.首先基于二维离散小波(2D-DWT)对图像进行二层小波变换,将所得的低频信息和水平、垂直和对角高频信息进行加权融合.在此基础上,采用二维主成分分析(2D-PCA)方法进行特征提取;最后采用最近邻分类器进行分类识别.基于ORL标准人脸数据库的实验结果表明,本文提出的方法比传统的2D-PCD识别算法和2D-DWT+2D-PCA识别算法有更好的识别效果,且人脸受光照等因素的影响表现出良好的鲁棒性.

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