基于matlab的人臉識別技術(shù)-資料下載頁
2025-08-19 14:21本頁面
【正文】 = Eigenfaces39。*A(:,i)。 ProjectedImages = [ProjectedImages temp]。 %得到 L_eig_vec。endInputImage = imread(TestImage)。%讀入測試圖片temp = rgb2gray(InputImage)。%取其中的一維來處理[irow icol] = size(temp)。%測試圖片大小InImage = reshape(temp,irow*icol,1)。%轉(zhuǎn)置后轉(zhuǎn)為一維Difference = double(InImage)m。 % L_eig_vec39。ProjectedTestImage = Eigenfaces39。*Difference。 % 測試圖像的特征向量Euc_dist = []。for i = 1 : Train_Number%對每列 q = ProjectedImages(:,i)。%取出訓(xùn)練圖像 temp = ( norm( ProjectedTestImage q ) )^2。%歐氏距離 Euc_dist = [Euc_dist temp]。%end[Euc_dist_min , Recognized_index] = min(Euc_dist)。%得到差值最小的圖像的索引號OutputName = strcat(int2str(Recognized_index),39。.jpg39。)。%得到文件名% A sample script, which shows the usage of functions, included in% PCAbased face recognition system (Eigenface method)%% See also: CREATEDATABASE, EIGENFACECORE, RECOGNITIONclear allclcclose all% You can customize and fix initial directory pathsTrainDatabasePath = uigetdir(39。D:\人臉庫\PCA_based Face Recognition System39。,... 39。Select training database path39。 )。TestDatabasePath = uigetdir(39。D:\人臉庫\\PCA_based Face Recognition System39。,... 39。Select test database path39。)。prompt = {39。Enter test image name (a number between 1 to 10):39。}。dlg_title = 39。Input of PCABased Face Recognition System39。num_lines= 1。def = {39。139。}。TestImage = inputdlg(prompt,dlg_title,num_lines,def)。TestImage = strcat(TestDatabasePath,39。\39。,char(TestImage),39。.jpg39。)。im = imread(TestImage)。T = CreateDatabase(TrainDatabasePath)。[m, A, Eigenfaces] = EigenfaceCore(T)。OutputName = Recognition(TestImage, m, A, Eigenfaces)。SelectedImage = strcat(TrainDatabasePath,39。\39。,OutputName)。SelectedImage = imread(SelectedImage)。imshow(im)title(39。測試圖像39。)。figure,imshow(SelectedImage)。title(39。識別圖像39。)。str = strcat(39。Matched image is : 39。,OutputName)。disp(st
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