morphological
binaryImage = grayImage > 150;maskedImage = zeros(size(grayImage)); % Initialize.
maskedImage(binaryImage) = grayImage(binaryImage);% Demo by ImageAnalyst
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables.
workspace; % Make sure the workspace panel is showing.
fontSize = 14;% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');baseFileName = 'coins.png';% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % File doesn't exist -- 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 in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endendgrayImage = imread(fullFileName);% Get the dimensions of the image.
% numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);% Display the original gray scale image.
subplot(2, 2, 1);imshow(grayImage, []);title('Original Grayscale Image', 'FontSize', fontSize);% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') % Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(grayImage);subplot(2, 2, 2); bar(pixelCount);grid on;title('Histogram of original image', 'FontSize', fontSize);xlim([0 grayLevels(end)]); % Scale x axis manually.
yl = ylim();line([150 150], [0 yl(2)], 'Color', 'r');% Threshold at 150
binaryImage = grayImage > 150;% Display the original gray scale image.subplot(2, 2, 3);imshow(binaryImage, []);title('Binary Image', 'FontSize', fontSize);% Mask the image
maskedImage = zeros(size(grayImage)); % Initialize.% Assign values from grayImage that are > 150.
maskedImage(binaryImage) = grayImage(binaryImage);% Display the original gray scale image.subplot(2, 2, 4);imshow(maskedImage, []);title('Masked Image', 'FontSize', fontSize);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 short g;format compact;fontSize = 25;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'netmuscle.jpg';% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);%===============================================================================% Read in a demo image.
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(:, :, 3); % Take blue channel.
end% Display the image.
subplot(1, 2, 1);imshow(grayImage, []);axis on;axis image;caption = sprintf('Original Gray Scale Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);% 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')drawnow;% Do a bottom hat filter to find the small dark spots.
subplot(1, 2, 2);histogram(grayImage);grid on;se = strel('disk', 15);filteredImage = imbothat(grayImage, se);% Display the image.imshow(filteredImage, []);histogram(filteredImage);grid on;% Binarize the image.
% binaryImage = imbinarize(grayImage);
binaryImage = filteredImage >35; % Dtermine number from histogram.
% Make sure there are blobs only between 100 and 800 pixels.
binaryImage = bwareafilt(binaryImage, [100, 800]);% Display the image.subplot(1, 2, 2);imshow(binaryImage, []);axis on;axis image;caption = sprintf('Binary Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Label the image
[labeledImage, numBlobs] = bwlabel(binaryImage);% Make measurements of bounding box
props = regionprops(labeledImage, 'Area');allAreas = [props.Area]sortedAread = sort(allAreas)caption = sprintf('Binary Image with %d Muscle Fibers', numBlobs);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
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