function eroded_image = erode2( source_image, neighborhood );
% ERODE2 erode a greyscale image.
%   eroded_image = erode2( source_image, neighborhood );
% erodes the image to make white objects smaller, black cracks larger,
% (The MatLab function "erode.m"
% does the same thing, but only accepts binary black-and-white image).
% Assumes source_image is a array 0 = black, max(source_image)=white pixels;
% Assumes neighborhood is a array of
% 1 = neighbor pixels, 0 = non-neighbor pixels;
% See also ERODE2, OPEN2, CLOSE2, DILATE.

% Change log:
% 1999-02-15:DAV: modified to avoid black frame creepage.
% 1998-03-26:DAV: updated to grayscale version.
% 1998-02-04:DAV: David Cary wrote binary version

% see medfilt2() for median filtering.

if( isa(source_image, 'uint8') ),
    the_max = double( max(source_image(:)) );
    
    % I thought this would be faster than converting back and forth to doubles,
    % but (according to 'profile') it is slightly slower.
    % elements = nnz(neighborhood);
    % % bitcmp(x, 8) = bitxor(x, 0xFF) = 0xFF - x.
    % eroded_image = bitcmp( ordfilt2(bitcmp(source_image, 8), elements, neighborhood), 8 );
    % eroded_image = bitxor( ordfilt2(bitxor(source_image, 255), elements, neighborhood), 255 );
    % It makes no difference whether "neighborhood"
    % is double or uint8.
    % neighborhood = uint8(neighborhood);
    
    eroded_image = uint8(ordfilt2(double(source_image) - the_max, 1, neighborhood) + the_max);
    
else,
    the_max = max(source_image(:));
    eroded_image = ordfilt2(source_image - the_max, 1, neighborhood) + the_max;
end
% end erode2.m