Sampling nodes equally to cover all the environment

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if i have this binary image, and i would like to distributed nodes in
the white area, which is the best way can distributed nodes to cover all the environments equally?
unifor.png
  4 Comments
Walter Roberson
Walter Roberson on 28 Jul 2019
As a first attempt, you could find() the row, column positions of all of the white pixels. Arrange as row column pairs as rows [r1 c1; r2 c2; ...]. Now kmeans requesting 50 clusters.
mohammed alany
mohammed alany on 28 Jul 2019
i am new in matlab
i perform this, how i can use kmeans now please?
map = imread('C:\Users\mrh\Desktop\a1.jpg');
BW = im2bw(map)
[y, x] = find(map)
c = [x, y]

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Accepted Answer

Walter Roberson
Walter Roberson on 30 Jul 2019
NC = 50;
map = imread('unifor.png');
BW = im2bw(map);
[y, x] = find(BW);
c = [x, y];
initpos = c(randperm(size(c,1),NC),:);
[idx,cents] = kmeans(c, NC, 'maxiter', 500, 'start', initpos);
ddd = squareform(pdist(cents));
ddd(1:(NC+1):end) = inf;
image(BW);
colormap(gray(2));
N = string(1 : NC);
hold on
scatter(cents(:,1), cents(:,2));
text(cents(:,1), cents(:,2), N);
hold off
You might notice some points at the bottom of the image. That white stripe along the bottom is part of the original image, and so distributing equally in the white portion requires placing some points in that white stripe.

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