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Detects multiple disks (coins) in an image using Hough Transform

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Detects multiple disks (coins) in an image using Hough Transform

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29 Dec 2008 (Updated )

HOUGHCIRCLES detects multiple disks (coins) in an image using Hough Transform.

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File Information
Description

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 = |x1-x2|+|y1-y2|+|r1-r2|

Output
  - circles: n-by-4 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.

Acknowledgements

This file inspired Tactics Toolbox.

Required Products Image Processing Toolbox
MATLAB release MATLAB 7.5 (R2007b)
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Comments and Ratings (13)
28 Feb 2013 Raz Shimoni

Thank you very much.

10 Apr 2011 Yuan-Liang Tang

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.

Yuan-Liang Tang

10 Apr 2011 Sushma Bhandari

im unable to detect the circles.what should be the minR and mixR,can anyone help me?

07 Dec 2009 Christoph  
30 Jul 2009 Nazatul Naquiah Ahba

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?

22 Jul 2009 Venugopalakrishna

Thank you very much.

15 Jul 2009 TUYEN Nguyen Ba

Thank you Prof. Yuan Liang Tang. This is really great!

11 Jun 2009 Yuan-Liang Tang

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, maxR-minR+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.

11 Jun 2009 sanjay bhattacharya

i used the houhcircles function. it says 'out of memory' for my test images; but it worked for very small binary images; please help

16 May 2009 Rezki Al Khairi

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..

06 Apr 2009 Idillus

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

06 Apr 2009 Idillus

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

07 Jan 2009 Sven

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.

Updates
29 Dec 2008

Description about the format of function invocation is corrected.

29 Dec 2008

Description of the format of function invocation is corrected.

31 Dec 2008

Major modifications of the program.

07 Jan 2009

Minor modifications according to Sven's suggestions. Thanks a lot, Sven.

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