MATLAB: Having difficulty in simple circle detection

find circleimfindcircles

Hi,

I am having difficulty finding a circle.

I already tried 'imfindcirles' , with different sensitivity but failed.

please help in this. i want to find the radius and center point of the dark blue circel (image attached).

Thanks in advance.

Best Answer

Use the Color Thresholder app on the apps tab of the tool ribbon. I'd use hsv color space. Then adjust the thresholds and Export the code into a new function m-file.

rgbImage = imread('Captur11.jpg');
subplot(2, 1, 1);
imshow(rgbImage);
[BW,maskedRGBImage] = createMask(rgbImage);
% Fill holes
BW = imfill(BW, 'holes');
% Take largest blob.
BW = bwareafilt(BW, 1);
subplot(2, 1, 2);
imshow(BW)
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 11-May-2020
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.584;
channel1Max = 0.619;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.856;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
	(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
	(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

Related Solutions

MATLAB: How to cut out annular of this Image

The code below works for this image. Of course it may not work if you change the lighting, exposure, camera angle, F-stop, or clutter (other stuff) in the image, and would need adaptation for those cases.

% Code to analyze grinding wheel
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%=======================================================================================
% Read in image.
fullFileName = fullfile(pwd, 'annular_orig.jpg');
[folder, baseFileName, ext] = fileparts(fullFileName);
rgbImage = imread(fullFileName);
% Shrink it to speed it up
% rgbImage = imresize(rgbImage, 0.75);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the original image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original Color Image "%s"', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.

% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
% Get mask for outer gray, and inner blue parts of the wheel by doing color segmentations.
[wheelMask,maskedRGBImage] = createMaskForWholeWheel(rgbImage);
[blueMask,maskedRGBImage] = createMaskForBlueCenter(rgbImage);
% Clean up noise by filling holes and taking largest blob only.
wheelMask = imfill(wheelMask, 'holes');
wheelMask = bwareafilt(wheelMask, 1);
blueMask = imfill(blueMask, 'holes');
blueMask = bwareafilt(blueMask, 1);
% Display the images.
subplot(2, 2, 2);
imshow(wheelMask);
axis on;
title('Total Wheel Mask', 'FontSize', fontSize, 'Interpreter', 'None');
subplot(2, 2, 3);
imshow(blueMask);
axis on;
title('Blue Center Mask', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Get the ring mask
ringMask = wheelMask & ~blueMask;
% Display the image.
subplot(2, 2, 4);
imshow(ringMask);
axis on;
title('Ring Mask', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Find boundaries
boundaries = bwboundaries(ringMask);
% Display the original image with mask boundary over it.
figure;
imshow(rgbImage, []);
axis on;
caption = sprintf('Color Image with Boundary');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Plot boundaries
hold on;
numberOfBoundaries = size(boundaries, 1);
for k = 1 : numberOfBoundaries
  thisBoundary = boundaries{k};
  plot(thisBoundary(:,2), thisBoundary(:,1), 'r', 'LineWidth', 3);
end
hold off;
% Get the equivalent circular diameters.
propsWheel = regionprops(wheelMask, 'EquivDiameter');
wheelDiameter = propsWheel.EquivDiameter
propsBlue = regionprops(blueMask, 'EquivDiameter');
blueDiameter = propsBlue.EquivDiameter
% Get the area of the ring and put it up on the image.
ringArea = sum(ringMask(:));
message = sprintf('Area of ring = %d pixels.\nAverage Diameter of Entire Wheel = %.1f pixels.\nAverage Diameter of Blue Part = %.1f pixels.\nAverage Thickness of Edge = %.1f pixels.', ...
  ringArea, wheelDiameter, blueDiameter, wheelDiameter-blueDiameter);
text(20, 150, message, 'FontSize', fontSize, 'Color', 'y', 'FontWeight', 'bold', 'VerticalAlignment', 'top');
function [BW,maskedRGBImage] = createMaskForWholeWheel(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.

%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using

%  auto-generated code from the colorThresholder app. The colorspace and

%  range for each channel of the colorspace were set within the app. The

%  segmentation mask is returned in BW, and a composite of the mask and

%  original RGB images is returned in maskedRGBImage.

% Auto-generated by colorThresholder app on 15-Aug-2018

%------------------------------------------------------

% Convert RGB image to chosen color space

I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings

channel1Min = 0.363;
channel1Max = 0.855;
% Define thresholds for channel 2 based on histogram settings

channel2Min = 0.000;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings

channel3Min = 0.000;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds

sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
  (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
  (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.

maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.

maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end
function [BW,maskedRGBImage] = createMaskForBlueCenter(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 15-Aug-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.569;
channel1Max = 0.671;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.229;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.251;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
  (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
  (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

MATLAB: Automatically segment the fish eye

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%=======================================================================================
% Have user browse for a file, from a specified "starting folder."
% For convenience in browsing, set a starting folder from which to browse.
% startingFolder = pwd;  % or 'C:\wherever';
% if ~exist(startingFolder, 'dir')
% 	% If that folder doesn't exist, just start in the current folder.
% 	startingFolder = pwd;
% end

% % Get the name of the file that the user wants to use.
% defaultFileName = fullfile(startingFolder, 'n*.*');
% [baseFileName, folder] = uigetfile(defaultFileName, 'Select a file');
% if baseFileName == 0
% 	% User clicked the Cancel button.
% 	return;
% end
folder = pwd;
baseFileName = 'IMG_Segment_Failed.JPG';
% baseFileName = 'IMG_Segment_Success.JPEG';
fullFileName = fullfile(folder, baseFileName);
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows1, columns1, numberOfColorChannels1] = size(rgbImage)
% Display the original image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis('on', 'image');
caption = sprintf('Original Color Image\n"%s"', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.



% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by Image Analyst', 'NumberTitle', 'Off')
[mask, maskedRGBImage] = createMask(rgbImage);
% Display the image.

subplot(2, 2, 2);
imshow(mask, []);
axis('on', 'image');
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Do area filtering.
mask = bwareafilt(mask, [30000, 60000]);
% Display the image.
subplot(2, 2, 3);
imshow(mask, []);
axis('on', 'image');
title('Mask Image after area filtering', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Measure things in the mask
labeledImage = bwlabel(mask);
props = regionprops(labeledImage, 'Area', 'Perimeter');
allAreas = [props.Area];
% sortedAreas = sort(allAreas)
allPerims = [props.Perimeter];
circularities = allPerims .^ 2 ./ (4 * pi * allAreas)
subplot(2, 2, 4);
% histogram(circularities);
% grid on;
% Extract the roundest blob - the one with circularity closest to 1
[~, index] = min(abs(circularities - 1))
mask = ismember(labeledImage, index);
imshow(mask, []);
axis('on', 'image');
title('Mask Image after circularity filtering', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 19-Dec-2019
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.254;
channel1Max = 0.991;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;
channel3Max = 0.523;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
	(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
	(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

It might need some tweaking to get it to work with all images.

Or you could try deep learning. I tried imfindcircles() and was not very successful with that function.

Best Answer

Related Solutions

MATLAB: How to cut out annular of this Image

MATLAB: Automatically segment the fish eye

Related Question