MATLAB: Detect defects (notches and breaks) in rubber O-rings

@image analystImage Processing Toolboximage segmentation

Hi,

I'm trying to detect defects (notches and breaks) in rubber O-rings. Tried many command: "imopen", "adapthisteq", "bwmorph", etc…they work on some images, but not on all of them. You'll realise that some backgrounds are not 100% clear, the shadow and rubber pieces (in some) are considered part of the object sometimes. I tried "graythresh" to sepatrate the object from the background, nothing works….any idea? you assistance would be apprciated.

images attached….

Sincerely,

Best Answer

Here is a more complete answer:

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 = 'oring03.jpg';
% 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, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Display histogram
subplot(2, 3, 2);
imhist(grayImage);
grid on;
title('Histogram of original gray image', 'FontSize', fontSize);
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
threshold = 100;
outerMask = grayImage < threshold;
outerMask = imfill(outerMask, 'holes');
outerMask = bwareafilt(outerMask, 1);
% Display the image.
subplot(2, 3, 3);
imshow(outerMask, []);
title('Outer Mask', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Measure area and solidity.

props = regionprops(outerMask, 'Area', 'Solidity', 'ConvexHull', 'EquivDiameter');
fprintf('Outer Area = %d pixels.  Outer Solidity = %.5f\n', props.Area, props.Solidity);
% Fit the convex hull perimeter to a circle.

[xCenter, yCenter, R, a] = FitCircle(props.ConvexHull(:, 1), props.ConvexHull(:, 2));
% Plot that circle in the overlay

hold on;
theta = linspace(0, 2*pi, 2 * (rows + columns));
x = R * cos(theta) + xCenter;
y = R * sin(theta) + yCenter;
plot(x, y, 'r-', 'LineWidth', 2);
% Make a mask of the circle.

circleMask = poly2mask(x, y, rows, columns);
% Do an xor with the mask to see where it's different.

differing = xor(circleMask, outerMask);
% Display the image.
subplot(2, 3, 4);
imshow(differing, []);
title('Non-Circular Parts', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Now get the inner circle.
innerMask = (grayImage >= threshold) & outerMask;
innerMask = imfill(innerMask, 'holes');
innerMask = bwareafilt(innerMask, 1);
% Display the image.
subplot(2, 3, 5);
imshow(innerMask, []);
title('Inner Mask', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Measure area and solidity.
props = regionprops(innerMask, 'Area', 'Solidity', 'ConvexHull', 'EquivDiameter');
fprintf('Inner Area = %d pixels.  Inner Solidity = %.5f\n', props.Area, props.Solidity);
% Fit the convex hull perimeter to a circle.
[xCenter, yCenter, R, a] = FitCircle(props.ConvexHull(:, 1), props.ConvexHull(:, 2));
% Plot that circle in the overlay
hold on;
theta = linspace(0, 2*pi, 2 * (rows + columns));
x = R * cos(theta) + xCenter;
y = R * sin(theta) + yCenter;
plot(x, y, 'r-', 'LineWidth', 2);
% Make a mask of the circle.
circleMask = poly2mask(x, y, rows, columns);
% Do an xor with the mask to see where it's different.
differing = xor(circleMask, innerMask);
% Display the image.
subplot(2, 3, 6);
imshow(differing, []);
title('Non-Circular Parts', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
function [xCenter, yCenter, R, a] = FitCircle(x,y)
% FitCircle() : Fits a circle in x-y plane.
% Result is center point (xCenter, yCenter) and radius R.  
% "a" is an optional output describing the circle's equation:%
%     x^2+y^2+a(1)*x+a(2)*y+a(3)=0       
% by Bucher izhak 25/oct/1991
n = length(x);  
xx = x.*x; 
yy = y.*y; 
xy = x.*y;
A = [sum(x) sum(y) n;sum(xy) sum(yy) sum(y);sum(xx) sum(xy) sum(x)];
B = [-sum(xx+yy) ; -sum(xx.*y+yy.*y) ; -sum(xx.*x+xy.*y)];
a = A\B;
xCenter = -.5*a(1);
yCenter = -.5*a(2);
R = sqrt((a(1)^2+a(2)^2)/4-a(3));
end

Related Solutions

MATLAB: Obtain average image threshold without the background

Try 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 = 'image.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, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255;  %imbinarize(grayImage);
subplot(2, 2, 2);
imshow(mask, []);
impixelinfo;
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Display histogram of image but only the image within the mask
subplot(2, 3, 4);
histogram(grayImage(mask), 0:255);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))
% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);
% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;
subplot(2, 3, 5);
imshow(brightStuff, []);
impixelinfo;
title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
subplot(2, 3, 6);
darkStuff = ~brightStuff & mask;
imshow(darkStuff, []);
impixelinfo;
title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;

MATLAB: Detection of Particle Orientation

Use regionprops():

% Code to detect angle of a blob.
% By Image Analyst
clc;    % Clear the command window.
fprintf('Beginning to run %s.m ...\n', mfilename);
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 = 15;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'ZoomIn_100f.jpg';
% 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(:, :, 1); % Take red channel.
end
% Crop it to the right lines.
% grayImage = grayImage(1750:2250, 800:end);
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
title('Red Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.

drawnow;
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Histogram of Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image by interactively thresholding using the function at
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image
% 91 seems good for this image.
lowThreshold = 91;
highThreshold = 255;
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage)
mask = grayImage > lowThreshold & grayImage < highThreshold;
mask = imclearborder(mask);
mask = imfill(mask, 'holes');
% Take largest blobs.
mask = bwareafilt(mask, 1);
subplot(2, 2, 3);
imshow(mask, []);
impixelinfo;
caption = sprintf('Mask of White SemiCircles');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
% Measure centroid and orientation.
props = regionprops(mask, 'Centroid', 'Orientation')
xCenter = props.Centroid(1);
yCenter = props.Centroid(2);
hold on;
plot(xCenter, yCenter, 'r+', 'MarkerSize', 40, 'LineWidth', 2);
% Display the masked image.
subplot(2, 2, 4);
overlayImage = imoverlay(grayImage, mask, 'r');
imshow(overlayImage, []);
impixelinfo;
caption = sprintf('Masked Image.  Angle = %.2f degrees.', props.Orientation);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Make a line at that angle at the centroid.
slope = tan(props.Orientation)
x = 1 : columns;
y = slope * (x - xCenter) + yCenter;
hold on;
plot(x, y, 'r-', 'LineWidth', 2);
fprintf('Done running %s.m ...\n', mfilename);

Best Answer

Related Solutions

MATLAB: Obtain average image threshold without the background

MATLAB: Detection of Particle Orientation

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