count particle statistics from image

count_particles.m

% image file
FILE_NAME = 'p2.png';

% length / pixel
LENGTH_SCALE = 500 / 114;

% ignore regions if area small than
MIN_AREA = 10;

% filter to create binary image
FILTER_VALUE = 128;



im = imread(FILE_NAME);
if (size(im, 3) == 1)
	bm = im;
else
	bm = rgb2gray(im);
end
figure(1)
fi = imshow(bm);

ui = imcontrast;
msgbox(['[i] adjust the contrast to display particles clearly, ' ...
	'then press "Adjust Data" and close the contrast window.'])
uiwait(ui);
mi = findobj(fi, 'Type', 'image');
bm = get(mi, 'Cdata');
bm = bm > 128;

ss = regionprops(bm, 'Basic');
px = arrayfun(@(s) s.Centroid(1), ss);
py = arrayfun(@(s) s.Centroid(2), ss);
pa = arrayfun(@(s) s.Area, ss);
ii = find(pa > MIN_AREA);
px = px(ii);
py = py(ii);

figure(2);
plot(px, py, '*');

tri = delaunay(px, py);
figure(3);
triplot(tri, px, py);

edges = [];
for ii = 1:length(tri)
	es = tri(ii, :);
	es2 = [es es(1)];
	for jj = 1:length(es);
		vi = es(jj);
		vj = es2(jj + 1);
		xi = px(vi); yi = py(vi);
		xj = px(vj); yj = py(vj);
		edges(end + 1) = sqrt((xi - xj)^2 + (yi - yj)^2);
	end
end

figure(4);
x = [0:10:200];
n = histc(edges, x / LENGTH_SCALE);
bar(x, n / 2);
xlim([min(x) max(x)]);
xlabel('distance (nm)');
ylabel('count')
set(gcf, 'color', 'w');