[Matlab] Image Dilation

% BI_dilate.m
% Binary Dilation operation
% Written by Barak Itkin, http://barak-itkin.blogspot.com

%%%%%%%%%%%%%%%%%%%% Image commands "cheat sheet" %%%%%%%%%%%%%%%%%%%%%%%%%

% im = imread (path);           % read an image file (try 'cameraman.tif'
%                               % and 'peppers.png')
% info = imfinfo (path);        % Get information about the image (use the
%                               % same path!). Try printing this ;)
%
% if info.ColorType == 'truecolor' % Check if the image is RGB type
%    img = rgb2gray(im);        % If so, convert to gray 0-255
% else                          % Otherwise (if gray), do nothing
%    img = im;                  % Nothing :)
% end                           % End of if statement
%
% imgd = img >= 128;            % Preform thresholding with a limit of 128
%                               % (127 or less => 0, 128 or more => 1)
% imshow (imgd);                % Display some image in rgb/gray/0-1/0-255

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%% BI_dilate (img, se) %%%
% img           = a black-white image (binary 2D array)
% se            = a binary array, where 1 is the area to match
% dimg (return) = the dilated image

% Example useage - imshow (BI_dilate (img, ones(3)))
function dimg = BI_dilate (img, se)

% Get the image width and height
[h,w] = size (img);

% Get the structure element width and height
[hse,wse] = size (se);

% The index of the middle of the structure elements
% For example, in a 3x5 matrix we'll have (2,3). Don't forget that matlab
% indexes begin in 1, and not in zero!
xm = 1 + floor(wse / 2);
ym = 1 + floor(hse / 2);

% Let's create a new image, from the source image, and pad it's edges
% This will save us index troubles for referencing indexes outside of the
% image on the edges.

% So, initialize the image with 0's (in dilation, we match 1', so
% initializing with 0's means it won't change the effect)
bigimg = zeros (size(img)+(size(se)-1));
% Now, copy the original image to the right place in the big image
bigimg(ym:(ym+h-1),xm:(xm+w-1)) = img;

% Create the result image
dimg = zeros(size(img));

% Pass over all pixels in the source image
for i=1:h
    for j = 1:w
        % Calculate the intersection of the se with the source image
        % - We intersect with bigimg which is our source image with padding
        %   on the edges to solve index problems on the edges
        % - We use the .* operator which means element-by-element
        %   multiplication (and not regular matrix multiplication)
        % - We multiply element-by-element by the SE, so that areas which
        %   had 1 in the SE will not change, and areas that had 0 will be
        %   ignored
        intersect = bigimg(i:(i+hse-1),j:(j+wse-1)) .* se;
        % Now, we check if the intersection wasn't zero, and we put that in
        % the result image
        dimg(i,j) = sum (intersect(:) == 1);
    end
end