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Calculating the coordinates for the center of a circle in an image

Question:

<img alt="enter image description here" class="b-lazy" data-src="https://i.stack.imgur.com/KxJEJ.jpg" data-original="https://i.stack.imgur.com/KxJEJ.jpg" src="https://etrip.eimg.top/images/2019/05/07/timg.gif" />

Say I have this image and I want to get the center of each circle in (X , Y).

Is there an algorithm to do so in MatLab??

Answer1:

Here is a result using cross-correlation with artificial circle as a filter. The result is [row, column] from upper left corner:

>> disp(centers) 483 1347 460 662 478 1001 451 290

There is no detailed comments, please ask it required.

im = rgb2gray(im2double(imread('D:/temp/circles.jpg'))); r = 117; % define radius of circles thres_factor = 0.9; % see usage %% [x, y] = meshgrid(-r : r); f = sqrt(x .^ 2 + y .^ 2) >= r; %% im = im - mean(im(:)); im = im / std(im(:)); f = f - mean(f(:)); f = f / std(f(:)) / numel(f); imf_orig = imfilter(im, f, 'replicate'); %% search local maximas imf = imf_orig; [n_idx, m_idx] = meshgrid(1 : size(imf, 2), 1 : size(imf, 1)); threshold = thres_factor * max(imf(:)); centers = []; % this is the result while true if max(imf(:)) < threshold break; end [m, n] = find(imf == max(imf(:)), 1, 'first'); centers = cat(1, centers, [m, n]); % now set this area to NaN to skip it in the next iteration idx_nan = sqrt((n_idx - n) .^ 2 + (m_idx - m) .^ 2) <= r; imf(idx_nan) = nan; end

<img alt="enter image description here" class="b-lazy" data-src="https://i.stack.imgur.com/pESPs.png" data-original="https://i.stack.imgur.com/pESPs.png" src="https://etrip.eimg.top/images/2019/05/07/timg.gif" />

Answer2:

That's possible with one call to <a href="http://www.mathworks.nl/help/images/ref/regionprops.html" rel="nofollow">regionprops</a>:

img = imread('KxJEJ.jpg'); % read the image imgbw = ~im2bw(img,graythresh(img)); % convert to grayscale stats = regionprops(bwlabel(imgbw), 'centroid','area'); % call regionprops to find centroid and area of all connected objects area = [stats.Area]; % extract area centre = cat(1,stats.Centroid); % extract centroids centre = centre(area>10,:); % filter out dust specks in the image

Now centre contains an Nx2 array: first column is x-position, second column is y-position of the centres:

centre = 289.82 451.73 661.41 461.21 1000.8 478.01 1346.7 482.98

Answer3:

I recall doing that at the university, <strong>many</strong> years ago!

What we did was to apply a threshold and make everything black and white. Then, we blobbed out the white area (non-circle) so it spread onto the circles.

When they started to disappear, we had the coordinates.

You could also pick two points at the circumference, find the exact middle of the line between them and then draw a perpendicular line through that point. If the middle of the new line <strong>is</strong> the center of the circle.

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