基于小波变换和主分量分析的人脸识别

Face Recognition Based on Wavelet Transform and Principal Component Analysis

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.

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.