Matrix deminatation are not agree error in this code.error in Minus ?temp = ( norm( ProjectedTestImage - q ) )^2;

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reema
reema 2014-8-6
img = imread('2.jpg');
img = rgb2gray(img);
[irow icol] = size(img);
temp = reshape(img',irow*icol,1); % Reshaping 2D images into 1D image vectors
m = mean(temp,2); % Computing the average face image m = (1/P)*sum(Tj's) (j = 1 : P)
Train_Number = size(img,2);
temp =Train_Number - m;
L = temp'*temp; % L is the surrogate of covariance matrix C=A*A'.
[V D] = eig(L); % Diagonal elements of D are the eigenvalues for both L=A'*A and C=A*A'.
L_eig_vec = [];
L_eig_vec = [L_eig_vec V];
Eigenfaces = Train_Number * L_eig_vec;
ProjectedImages = [];
Train_Number = size(Eigenfaces,2);
temp = Eigenfaces'*Train_Number; % Projection of centered images into facespace
ProjectedImages = [ProjectedImages temp];
temp = Eigenfaces'*Train_Number; % Projection of centered images into facespace
ProjectedImages = [ProjectedImages temp];
%%%%%%%%%%%%%%%%%%%%%%%% Extracting the PCA features from test image InputImage = imread('2.jpg'); img = rgb2gray(InputImage);
temp = img(:,:,1);
[irow icol] = size(temp); InImage = reshape(temp',irow*icol,1); inputImage = size(InImage,2); Difference = double(inputImage)-m;% Centered test image ProjectedTestImage = Eigenfaces'*Difference; % Test image feature vector
Euc_dist = [];
q = ProjectedImages(:);
temp = ( norm( ProjectedTestImage - q ) )^2;
Euc_dist = [Euc_dist temp];
[Euc_dist_min , Recognized_index] = min(Euc_dist); OutputName = strcat(int2str(Recognized_index),'.jpg');

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