MATLAB: Function: imfindcircles detects false circles.

Image Processing Toolboximfindcircles

I have come across this a few times. The function imfindcircles detects false circles (like at the corners shown below) even when there is no pixel intensity variation at those places. What could the reason be? How can I avoid this? Are there any other suitable methods to find circles apart from this?

I have attached an example image.

This is my code:

clear all;
close all;
A = imread('synthetic_img3.png');
BW1 = bwmorph(im2bw(A),'close');
figure;
imshow(BW1)
[centers,radii] = imfindcircles(BW1,[5,500]);
figure, imshow(BW1);
hold on
viscircles(centers, radii,'EdgeColor','b');

The resulting output:

Best Answer

If you want to segment out the small circles, you could also use thresholding and size filtering (use imclearborder and bwareaopen) instead of imfindcircles(). Then you could do things like find area, perimeter, location, etc. with regionprops().

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MATLAB: Crop dark area and display the face only

Convert to grayscale and then threshold and find the bounding box

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Read in the color image.
folder = pwd;
baseFileName = 'm2.bmp';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 3, 1);
imshow(rgbImage, []);
axis on;
title('Original Color Image', 'FontSize', fontSize);
drawnow;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);
grayImage = rgb2gray(rgbImage);
imshow(grayImage, []);
title('Gray Scale version', 'FontSize', fontSize);
subplot(2, 3, 3);
histogram(grayImage(grayImage<255))
grid on;
title('Histogram of Gray Scale Image', 'FontSize', fontSize);
someThresholdValue = 150;
binaryImage = grayImage > someThresholdValue;
% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);
subplot(2, 3, 4);
imshow(binaryImage);
grid on;
title('Binary Image', 'FontSize', fontSize);
% Label the binary image.
labeledImage = bwlabel(binaryImage);
props = regionprops(labeledImage, 'BoundingBox');
bbox = props.BoundingBox
croppedImageRGB = imcrop(rgbImage, bbox);
subplot(2, 3, 5);
imshow(croppedImageRGB);
grid on;
title('Cropped RGB Image', 'FontSize', fontSize);
% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);
subplot(2, 3, 6);
imshow(croppedImageGray);
grid on;
title('Cropped Gray Scale Image', 'FontSize', fontSize);

MATLAB: Separate two type of object in the image

Do you mean like this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'Q4_4.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, 'file')
		% Still didn't find it.  Alert user.
		errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
		uiwait(warndlg(errorMessage));
		return;
	end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	% grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 3, 1);
imshow(grayImage);
axis('on', 'image');
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
% Binarize the image.
binaryImage = ~imbinarize(grayImage);
% Get rid of particles less than 200 in area.
binaryImage = bwareaopen(binaryImage, 200);
% Eliminate partial blobs - those touching the edge of the image.
binaryImage = imclearborder(binaryImage);
subplot(2, 3, 2);
imshow(binaryImage, []);
axis('on', 'image');
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
drawnow;
% Find blobs
props = regionprops(binaryImage, 'Centroid', 'Area');
xy = vertcat(props.Centroid)
allAreas = [props.Area];
subplot(2, 3, 3);
histogram(allAreas, 10);
grid on;
title('Histogram of Blob Areas', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Area', 'FontSize', fontSize, 'Interpreter', 'None');
ylabel('Count', 'FontSize', fontSize, 'Interpreter', 'None');
% Get blobs smaller than 2500
[labeledImage, numBlobs] = bwlabel(binaryImage);
smallIndexes = find(allAreas < 2500);
largeIndexes = find(allAreas >= 2500);
% Extract the small blobs with ismember()
smallBlobs = ismember(labeledImage, smallIndexes);
subplot(2, 3, 4);
imshow(smallBlobs);
title('Small Blobs', 'FontSize', fontSize, 'Interpreter', 'None');
% Extract the large blobs with ismember()
largeBlobs = ismember(labeledImage, largeIndexes);
subplot(2, 3, 5);
imshow(largeBlobs);
title('Large Blobs', 'FontSize', fontSize, 'Interpreter', 'None');

Best Answer

Related Solutions

MATLAB: Crop dark area and display the face only

MATLAB: Separate two type of object in the image

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