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基于小波变换和主分量分析的人脸识别
引用本文:张洪亮,李香玲,李晨璞,马丽红,闫常丽.基于小波变换和主分量分析的人脸识别[J].河北建筑工程学院学报,2010,28(1):126-128.
作者姓名:张洪亮  李香玲  李晨璞  马丽红  闫常丽
作者单位:河北建筑工程学院
基金项目:张家口市科技局指导性计划项目 
摘    要:提出了基于小波变换和主分量分析的人脸识别算法.该算法首先用小波变换对人脸图像进行小波分解,形成低频小波子图,然后用主分量分析法构造特征脸子空间,将人脸图像在特征空间的投影作为KNN分类器的输入,由KNN分类器对提取的特征进行识别.在ORL人脸数据库上的实验结果表明该方法具有良好的性能.

关 键 词:人脸识别  小波变换(WT)  主分量分析(PCA)  KNN分类器

Face Recognition Based on Wavelet Transform and Principal Component Analysis
Zhang Hongliang,Li Xiangling,Li Chenpu,Ma Lihong,Yan Changli.Face Recognition Based on Wavelet Transform and Principal Component Analysis[J].Journal of Hebei Institute of Architectural Engineering,2010,28(1):126-128.
Authors:Zhang Hongliang  Li Xiangling  Li Chenpu  Ma Lihong  Yan Changli
Affiliation:Hebei Institute of Architecture and Civil Engineering
Abstract:Wavelet transform combined with principal component analysis is applied to human face recognition. After extracting low frequency sub-band of face image in wavelet transform,the eigenface is constructed by PCA.Then all samples are projected into the subspace,the coefficient of every sample is inputted K-Nearest Neighbor,and the face recognizer consists of KNN.The experiments on ORL face database indicate that the recognition ratio is greatly improved.
Keywords:face recognition  wavelet transform(WT)  principal component analysis(PCA)  K-Nearest Neighbor(KNN)
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