Sampling nodes equally to cover all the environment
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mohammed alany
le 28 Juil 2019
Commenté : mohammed alany
le 30 Juil 2019
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](https://www.mathworks.com/matlabcentral/answers/uploaded_files/231650/unifor.png)
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Walter Roberson
le 28 Juil 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.
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Walter Roberson
le 30 Juil 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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