MATLAB: How to calculate the spreading length of an image of a droplet spreading and find the ROI and automate the process

digital image processingimage analysisimage processingImage Processing Toolboximage segmentationMATLABplot

I have a series of images of droplet impacting on another droplet. The images are in RGB color and I converted to grayscale and binarizeid it. Now from the code (using 'ginput') given below I could calculate the pixel distance from end to end of the horizontal spreading part. But I have a series (50 images) of images where the spread length is changing continously. Hence I need to identify a ROI and from that calculate the spreading distance automatically. How do I do so? Does 'ginput' give the pixel distance accurately after pointing and clicking on the two extremeties of white zone in the binary image?

clc;clear;
folder = 'C:\Users\Pragyan\Documents\MATLAB\Image processing';
baseFileName = '0.25_cmc_2mm_8_bit.jpg';
fullFileName = fullfile(folder, baseFileName);
[grayImage,map] = imread(fullFileName);
%impixelinfo;
grayImage = rgb2gray(grayImage);
imshow(grayImage,map)
binaryImage = ~imbinarize(grayImage);
imshow(binaryImage)
[x y]=ginput(6);
x=round(x);
y=round(y);
image_dist=sqrt((x(2)^2-x(1)^2)+y(2)^2-y(1)^2)

Best Answer

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 = 18;
folder = 'C:\Users\Pragyan\Documents\MATLAB\Image processing';
baseFileName = '0.25_cmc_2mm_8_bit.jpg';
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~isfile(fullFileName)
	% 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
	fullFileName = fullFileNameOnSearchPath;
end
[grayImage,map] = imread(fullFileName);
grayImage = rgb2gray(grayImage);
imshow(grayImage,map)
binaryImage = ~imbinarize(grayImage);
% Erase from line 758 down:
binaryImage(758:end, :) = false;
% Fill holes.
binaryImage = imfill(binaryImage, 'holes');
% Get rid of any msall noise blobs.
binaryImage = bwareafilt(binaryImage, 1); % Take largest blob only.
imshow(binaryImage)
impixelinfo;
props = regionprops(binaryImage, 'BoundingBox');
spreadingWidth = props.BoundingBox(3)
rectangle('Position', props.BoundingBox, 'Edgecolor', 'g', 'LineWidth', 2)
fprintf('Done running %s.m ...\n', mfilename);

If it doesn't work, let me know what went wrong.

Related Solutions

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');

MATLAB: Measure the spreading length using image analysis.

Try this:

% By Image Analyst
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 = 'spreading.jpeg';
% 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
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.

drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image
binaryImage = ~imbinarize(grayImage);
% Extract 3 largest blobs only.
binaryImage = bwareafilt(binaryImage, 3);
subplot(2, 2, 2);
imshow(binaryImage, []);
impixelinfo;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Get the bounding boxes
props = regionprops(binaryImage, 'BoundingBox');
allBB = vertcat(props.BoundingBox)
% Find out which is on top.
y = allBB(:, 2)
[sortedY, sortOrder] = sort(y, 'ascend')
% Sort props the same way.
allBB = allBB(sortOrder, :)
allWidths = allBB(:, 3)
allHeights = allBB(:, 4)
subplot(2, 2, 3);
bar(allWidths);
grid on;
title('Blob Widths', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Blob Number', 'FontSize', fontSize, 'Interpreter', 'None');
ylabel('Width', 'FontSize', fontSize, 'Interpreter', 'None');
subplot(2, 2, 4);
bar(allHeights);
grid on;
title('Blob Heights', 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Blob Number', 'FontSize', fontSize, 'Interpreter', 'None');
ylabel('Height', 'FontSize', fontSize, 'Interpreter', 'None');

Best Answer

Related Solutions

MATLAB: Separate two type of object in the image

MATLAB: Measure the spreading length using image analysis.

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