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

    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');