Circle detection using imfindcircle

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Hi to all, I'am trying to detect circle in this image using this:
[centerPoints, radius] = imfindcircles(newImage ,[2 30],'ObjectPolarity','dark','Sensitivity',0.98);
As you can see I'am in a very high Sensitivity looking for circles in this image but it won't find my circle in Wheat Color just the one in back with black line.
Also I have tried with some color enhancement but it won't work.

Accepted Answer

John BG
John BG on 17 Jan 2017
Hello Kika
I found a way to spot the inner circle:
1.
capture
A=imread('im1.jpg');
figure(1);h1=imshow(A);
2.
running the cursor around the picture one realises the circle you are after is slightly 'yellow'.
a saturated yellow would be: Yellow = Red + Green [1 1 0]
but this is a rather mild yellow, meaning that the red and green layers of the image are only between 15 and 35 points above the blue layer across the points of interest.
Let's catch these slightly yellow pixels:
A13=A(:,:,1)-A(:,:,3);A23=A(:,:,2)-A(:,:,3);
[x13,y13]=find(A13>30);
% [x23,y23]=find(A23>20);
% x=intersect(x13,x23);y=intersect(y13,y23);
figure(2);imshow(A)
hold all
figure(2);h1=plot(y13,x13,'y*')
3.
one could go now for the function imfindcircles that automates fitting circles, but instead of start guessing what parameters of this function would be the right ones, I chose to do a it manually, a bit a of exercise cannot harm, can it?
A2=A;
A2(x13,y13,1)=255;A2(x13,y13,2)=255;A2(x13,y13,2)=0;
figure(3);h1=imshow(A2);
4.
the square is fairly centred, so all left is to plot a circle
r=floor(mean([abs(min(x13)-max(x13)) abs(min(y13)-max(y13))])/2);
xc=floor(.5*abs(min(x13)+max(x13)));
yc=floor(.5*abs(min(y13)+max(y13)));
figure(1);plot(yc,xc,'g*')
da=1;a=[0:da:360];
px=r*cosd(a)+yc;py=r*sind(a)+xc;
figure(1);plot(px,py,'ro')
dear Kika
either with imfindcircles or shanks mare, the result is the same, you catch the inner circle.
if you find these lines useful would you please be so kind to mark my answer as Accepted Answer?
To any other reader, if you find this answer of any help please click on the thumbs-up vote link,
thanks in advance for time and attention
John BG
.
additional comment:
1.
it turns out that the mildly yellow points can only be spotted with the variance of the RGB layers
figure(4);varA=surf(var(double(A),0,3));
.
use the Rotate 3D function in the figure window to move the point of view and appreciate the target circle right on the hill that generates the variance for this picture
.
I tried different variance thresholds
vA=varA.CData;
m=255/max(max(vA));
figure(5);imshow(m*vA);
% try var threshold at 500
[x500,y500]=find(vA>500);
hold all;
figure(1);plot(x500,y500,'r*')
% try var threshold at 400
[x400,y400]=find(vA>400);
hold all;
figure(6);plot(x400,y400,'b*')
but the above lines give a better result
  3 Comments
John BG
John BG on 8 Apr 2018
Sure, please post it on another question, ok?
Let me the link to the new question, either by email or make a note here.
John BG
John BG on 8 Apr 2018
I have almost completed the solution for the tree rings counting.
If you post a new question with the tree trunk cross section and let me know the link I will post my answer as soon as you let me know.
Regards
John BG

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More Answers (2)

Image Analyst
Image Analyst on 16 Jan 2017
You already asked this and John and I answered and you accepted John's answer. Did it not work? Or not work for this particular color?
How many circles do you want from the image? I can see 1, 2, or 3 depending on how you define a circle. The gray ring consists of two circles, an inner one and an outer one, though they're not complete.
You haven't given the context for what you're doing. Why do you need to find circles? For example if you're looking at a 96 well plate, then simply put your plate into a jig/bracket, snap a picture of it and have a template to look in the same locations all the time. Why bother finding them if they don't move around? Just use a template/mask. For example you could take a blank shot, determine colors in the circles of the template, then take a sample image with stuff in there and compute Delta E to see how much it changed.
  6 Comments
Jan
Jan on 17 Jan 2017
@John BG: A figure or axes handle would not be useful, because both can contain multiple images. Therefore an image handle could be an option instead of providing the image data directly.
I do not see the reason for your "strongly recommended not to reveal work details" comment. What is the connection to this thread?
Image Analyst
Image Analyst on 17 Jan 2017
Now that we know the larger context of him trying to use computer vision to determine disc placement on a Nine Men's Morris playing board, I don't know how knowing the centroid of a playing piece is relevant. Like I've said before, just use a template and determine presence or absence of a playing piece. For example if you wanted to determine occupancy of stadium seats, would you try to determine the hair color and sex of the person occupying a seat? No, it doesn't matter - all that matters is that a seat is occupied. If you had a parking vacancy program and were looking at parking spaces, do you care if the space holds a Ford or a Honda? No, it doesn't matter so don't spend time trying to figure it out. All that matters is if a space is taken or not.

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Laura Achola
Laura Achola on 19 Sep 2022
Try [centerPoints, radius] = imfindcircles(newImage ,[2 30],'ObjectPolarity','bright','Sensitivity',0.98);
I think the issue is that you are using the foreground as dark instead of bright. You won't need the high sensitivity in that case.

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