基于PCA算法的人脸识别matlab程序

运行example，非常有意思的一个人脸识别程序。训练集有10个人，20张图片。测试集有这10个人的另外10张照片。 你选择任何一张测试，它都能从训练集中找到对应的那个人的照片，并显示出来。 【训练步骤】： L = A'*A; %20*20 [V D] = eig(L); %求特征值和特征向量 L_eig_vec = [L_eig_vec V(:,i)]; %求主分量(20,15) Eigenfaces = A * L_eig_vec; %求特征脸(200*180,20)*(20,15)=(200*180,15) 【识别步骤】： 识别步骤： temp = Eigenfaces'*A(:,i); % 训练集向特征向量投影 (15,200*180)*(200*180,1)=(15,1) ProjectedImages = [ProjectedImages temp]; %(15,20) ProjectedTestImage = Eigenfaces'*Difference; % 测试样本向特征向量投影(15,200*180)*(200*180,1)=(15,1) temp = ( norm( ProjectedTestImage - q ) )^2;%计算测试样本与每个训练样本的距离 投影后每个样本都是15维的向量。 'Eigenface' Face Recognition System Written by: Amir Hossein Omidvarnia Email: aomidvar@ece.ut.ac.ir This package implements a well-known PCA-based face recognition method, which is called 'Eigenface' [1]. All functions are easy to use, as they are heavy commented. Furthermore, a sample script is included to show their usage. In general, you should follow this order: 1. Select training and test database paths. TrainDatabasePath ='C:\Documents and Settings\dell1\桌面\PCA_based Face Recognition System\TrainDatabase'; 2. Select path of the test image. TestDatabasePath ='C:\Documents and Settings\dell1\桌面\PCA_based Face Recognition System\TestDatabase'; 3. Run 'CreateDatabase' function to create 2D matrix of all training images. T = CreateDatabase(TrainDatabasePath) 4. Run 'EigenfaceCore' function to produce basis's of facespace. [m, A, Eigenfaces] = EigenfaceCore(T) 5. Run 'Recognition' function to get the name of equivalent image in training database. OutputName = Recognition(TestImage, m, A, Eigenfaces) For your convenience, I have prepared sample training and test databases, which are parts of 'face94' Essex face database [2]. You just need to copy the above functions, along with the training and test databases into a specified path (for example 'work' path of your MATLAB root). Then follow dialog boxes, which will appear upon running 'example.m'. Enjoy it! References: [1] P. N. Belhumeur, J. Hespanha, and D. J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. In ECCV (1), pages 45--58, 1996. [2] Available at: http://cswww.essex.ac.uk/mv/allfaces/faces94.zip