I would like to apply a mask on the channels (semicircles) so it can be excluded from analysis of cell distribution (figure attached). I am required to apply a mask for 120 images, is it possible to read and write as well as apply the mask to all 120 images?
MATLAB: Applying the same mask on a set of images
image analysisimage processingImage Processing Toolbox
Related Solutions
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; endendgrayImage = 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);
See my Image Segmentation Tutorial. My File Exchange
What I might do is to use bwskel() to get the length of the crack. Then use regionprops() to get the area. Then divide the two to get the mean width. Also search the forum for cracks - it's been seen here several times before.
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