MATLAB: How to perform automatic conversion of matrix dimensions of images in a way that it works for both rgb and grayscale ?

Question

To perform face recognition, i have a train database with some images. The images in train database need to be pre-processed before they are used for comparison with the test image, which is the input image.

This is what i have done :

    T = [];
    for i = 1 : Train_Number
    str = int2str(i);
    str = strcat('\',str,'.jpg');
    str = strcat(TrainDatabasePath,str);
    img = imread(str);
    img = rgb2gray(img);
    img = imresize(img, [200 180]);
    [irow icol] = size(img);    
    temp = reshape(img',irow*icol,1);  
    % temp = reshape(permute(double(img), [2,1,3]), irow*icol, 1);
    T = [T temp]; % 'T' grows after each turn                    
    end

This works fine when the train database contains only rgb images. But for grayscale images, it gives error related to dimensions.

How can i make it work for both rgb and grayscale ??

Answer 1

Some cleanup and an implicit conversion of grayscale images to pseudo-RGB:

    nCol = 200;
    nRow = 180;
    % BUG?! T    = nan(nCol * nRow, Train_Number);  % Pre-allocate!!!
    T    = nan(nCol * nRow * 3, Train_Number);  % Pre-allocate!!! [EDITED]
    for i = 1 : Train_Number
       filename = fullfile(TrainDatabasePath, sprintf('%d.jpg', i));
       img = imread(filename);
       if ndims(img) == 2                       % Gray scale image:
          img = double(cat(3, img, img, img));  % Pseudo RGB image
       end
       img = imresize(img, [nCol, nRow]);
       temp = permute(img, [2,1,3]);
       T(:, i) = temp(:);
    end

But, I do not expect that the training of a face recognition system is efficient, when you feed it with RGB and gray-scale images. I'd prefer converting the RGB to gray scale instead.

img = rgb2gray(img);