MATLAB: How to cut out annular of this Image

annularcirclesection

Hello,

i want to cut out everything but the annular in between the red circles and display that in an axes.

Heres the original image:

Best Answer

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

Related Solutions

MATLAB: What is the fit method to exclude the shadow?

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;
%=======================================================================================
% Read in image.
fullFileName = fullfile(pwd, '63.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.
[mask, maskedRGBImage] = createMask(rgbImage);
% Clean up noise by filling holes and taking largest blob only.
mask = imfill(mask, 'holes');
mask = bwareafilt(mask, 1);
% Display the mask image.
subplot(2, 2, 2);
imshow(mask);
axis on;
title('Mask, binary image', 'FontSize', fontSize, 'Interpreter', 'None');
% Mask the image and show the masked image.
subplot(2, 2, 3);
imshow(maskedRGBImage, []);
axis on;
title('Masked RGB image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Display the original image with mask boundary over it.
subplot(2, 2, 4);
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
boundaries = bwboundaries(mask);
hold on;
numberOfBoundaries = size(boundaries, 1);
for k = 1 : numberOfBoundaries
  thisBoundary = boundaries{k};
  plot(thisBoundary(:,2), thisBoundary(:,1), 'r', 'LineWidth', 3);
end
hold off;
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 20-Aug-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.959;
channel1Max = 0.099;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.194;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.410;
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

Notes: It's not perfect because you don't have good control over your image capture situation. Get rid of shadows and background clutter to get a better masking.

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;

Best Answer

Related Solutions

MATLAB: What is the fit method to exclude the shadow?

MATLAB: Obtain average image threshold without the background

Related Question