Beam spot analysis Matlab script

BSA_process_directory.m

function BSA_process_directory(path)
  path = strcat(path, '\');

  % Filter only camera PNGs.
  files = dir(strcat(path, 'Frame_*.png'));

  % Create a Gaussian filter. This will be used 
  % to blur the image slightly so that spots 
  % form contiguous regions which can be 
  % analysed.
  G = fspecial('gaussian',[5 5],3);

  output = table();
  for file = files'
      
    image = imread(strcat(path, file.name));
    
    % Check for saturation.
    if BSA_is_saturated(image);
      disp(strcat('WARNING!  ', file.name,...
           ' is saturated! ',...
           'Relative intensities may be ',...
           'inaccuate.'));
    end;
        
    image = rgb2gray(image);

    image = imfilter(image, G, 'same');

    % Create a mask for the image regions. 
    % Cutoff is 10% the difference between max
    % and mean values.
    lower_bound = single(max(max(image))...
                  - mean(mean(image))) / ...
                  (10 * 255);
    bw = im2bw(image, lower_bound);

    % Calculate the properties for each region.
    stats = regionprops(bw, image, ...
      'Centroid',...
      'Area',...
      'MeanIntensity',...
      'PixelValues');

    length = size(stats);
    for i=1:length(1);
      name_arr = strsplit(file.name, {'_','.'});
      stats(i).FrameNo = name_arr(2);
      stats(i).SumIntensity = sum(stats(i).PixelValues);
      stats(i).SIError = sqrt(stats(i).Area * 0.5 ^ 2);
    end;
    stats = rmfield(stats,'PixelValues');

    stats = orderfields(stats, [4,2,5,6,1,3]);
    cells = struct2table(stats);
    output = [ output; cells ];
  end;
  output.Properties.VariableNames = {...
    'FrameNo',...
    'Centroid',...
    'SumIntensity',...
    'SIError',...
    'Area',...
    'MeanIntensity'};

  % Remove regions which comprise of less than 
  % 10000 pixels.
  output( output.Area < 10000,:) = [];
    
  writetable(output, strcat(path, 'maxima.csv'));
end