Created
September 10, 2015 17:19
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Beam spot analysis Matlab script
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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 |
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