HOUGHCIRCLES detects multiple disks (coins) in an image using Hough Transform. The image contains separating, touching, or overlapping disks whose centers may be in or out of the image.
Syntax
houghcircles(im, minR, maxR);
houghcircles(im, minR, maxR, thresh);
houghcircles(im, minR, maxR, thresh, delta);
circles = houghcircles(im, minR, maxR);
circles = houghcircles(im, minR, maxR, thresh);
circles = houghcircles(im, minR, maxR, thresh, delta);
Inputs:
 im: input image
 minR: minimal radius in pixels
 maxR: maximal radius in pixels
 thresh (optional): the minimal ratio of the number of detected edge pixels to 0.9 times the calculated circle perimeter (0<thresh<=1, default: 0.33)
 delta (optional): the maximal difference between two circles for them to be considered as the same one (default: 12); e.g., c1=(x1 y1 r1), c2=(x2 y2 r2), delta = x1x2+y1y2+r1r2
Output
 circles: nby4 array of n circles; each circle is represented by (x y r t), where (x y), r, and t are the center coordinate, radius, and ratio of the detected portion to the circle perimeter, respectively. If the output argument is not specified, the original image will be displayed with the detected circles superimposed on it.
Randy Tang (2020). Detects multiple disks (coins) in an image using Hough Transform (https://www.mathworks.com/matlabcentral/fileexchange/22543detectsmultiplediskscoinsinanimageusinghoughtransform), MATLAB Central File Exchange. Retrieved .
1.5.0.0  Minor modifications according to Sven's suggestions. Thanks a lot, Sven. 

1.3.0.0  Major modifications of the program. 

1.2.0.0  Description of the format of function invocation is corrected. 

1.1.0.0  Description about the format of function invocation is corrected. 
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nithi (view profile)
ty
Raz Shimoni (view profile)
Thank you very much.
Randy Tang (view profile)
Sushma,
minR and maxR are the minimal and maximal radii (in pixels), respectively, of the circles that you want to detect in your image. For the image I provided along with the program, I set minR=20 and maxR=40. If you still have problems, you may want to provide your image and I'll look into the problem.
YuanLiang Tang
Sushma Bhandari (view profile)
im unable to detect the circles.what should be the minR and mixR,can anyone help me?
Christoph (view profile)
Nazatul Naquiah Ahba (view profile)
hi, i've ran this code and it works. i wonder which part of the code display as accumulation array? can you pls guide me how to create the accumulation array from this code in order to generate the output figure of hough transform accumulation array?
Venugopalakrishna (view profile)
Thank you very much.
TUYEN Nguyen Ba (view profile)
Thank you Prof. Yuan Liang Tang. This is really great!
Randy Tang (view profile)
sanjay,
The most probable cause might be that you invoked the function using inappropriate parameters. The function allocate a 3D matrix of size [size(im,1)+maxR, size(im,2)+maxR, maxRminR+1], where minR and maxR are the minimal and maximal radii of circles you want to detect, respectively. You may want to check if the size of your input image or the values of minR and maxR are really huge.
sanjay bhattacharya (view profile)
i used the houhcircles function. it says 'out of memory' for my test images; but it worked for very small binary images; please help
Rezki Al Khairi (view profile)
i've try to make with GUI...
but i cannot place where the instrustion mace be placed...
can u help me pleasee...
i really need it..
Idillus (view profile)
Sorry, I've made ma mistake
if (nargin >=3  nargin <= 6)
if nargin==3
thresh = 0.33; % One third of the perimeter
delta = 12; % Each element in (x y r) may deviate approx. 4 pixels
edgeim = edge(im, 'canny', [0.15 0.2]);
end
if nargin==4
edgeim = edge(im, 'canny', [0.15 0.2]);
delta = 12;
end
if (nargin==5)
edgeim = edge(im, 'canny', canny_th);
delta = 12;
end
if (nargin==6)
edgeim = edge(im, 'canny', canny_th,sigma);
delta=12;
end
if (nargin == 7)
edgeim = edge(im, 'canny', canny_th,sigma);
end
end
if minR<0  maxR<0  minR>maxR  thresh<0  thresh>1  delta<0  canny_th <0  canny_th >1
disp('Input conditions: 0<minR, 0<maxR, minR<=maxR, 0<thresh<=1, 0<delta');
return;
end
Idillus (view profile)
Hi, nice function. I've made some changes that may be interesting. It wold be nice to change the threshold and sigma value for canny edge detection, so, I added a few lines to improve this, changing the location of the definition of the edgeimage
if nargin==3
thresh = 0.33; % One third of the perimeter
delta = 12; % Each element in (x y r) may deviate approx. 4 pixels
edgeim = edge(im, 'canny', [0.15 0.2]);
elseif nargin==4
if ((max(size(canny_th) == 2))  (max(size(canny_th) == 1)))
if max(size(canny_th) == 2)
edgeim = edge(im, 'canny', [canny_th(1) canny_th(2)]);
end
if max(size(canny_th) == 1)
edgeim = edge(im, 'canny', canny_th(1));
end
end
delta = 12;
else (nargin==5)
if ((max(size(canny_th) == 2))  (max(size(canny_th) == 1)))
if (max(size(canny_th) == 2))
edgeim = edge(im, 'canny', [canny_th(1) canny_th(2)],sigma);
end
if (max(size(canny_th) == 1))
edgeim = edge(im, 'canny', canny_th(1),sigma);
end
end
delta = 12;
end
Sven (view profile)
Nice function. Code is well documented and clearly written.
One suggestion is to follow the example of the peaks() function: if no output argument is given, then create a figure and display the image. If it's used with an output argument, assume the user is embedding the function in their own code, and doesn't want a figure to come up automatically.