Measure the spreading length using image analysis.
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In the attached image there are three figures where the spreading length is changing. How can I measure the spreading length of a set of images?
采纳的回答
Image Analyst
2020-6-23
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');
3 个评论
naygarp
2021-6-8
Hello, I have a similar type of problem. I have a series of images of droplet impacting on another droplet. The images are in RGB color but I converted to grayscale and binarizeit it. Now how do I measure the distance between the two ends from the binarized image supposing that I know a scale of '78 pixels/mm' in the image. From the above code I couldnot figure out the calculation part. Also how to automate it for a large number of image files where the spread increases continously.
clc;clear;
folder = 'I:\converted images\0.5\0.5 2 mm offset';
baseFileName = '0.5 cmc 2mm off0001.tif';
fullFileName = fullfile(folder, baseFileName);
[grayImage,map] = imread(fullFileName);
%impixelinfo;
grayImage = rgb2gray(grayImage);
%[img,map] = imread(fname,k)
imshow(grayImage,map)
binaryImage = ~imbinarize(grayImage);
imshow(binaryImage)
Image Analyst
2021-6-8
@naygarp, see the FAQ:
Start your own question if you need more help. And attach your images and code.
naygarp
2021-6-9
Thanks, I have posted my query as a separate question and I am sharing the link here
更多回答（1 个）
KALYAN ACHARJYA
2020-6-21
Two ways: I am considering the pixel distance length based on spaial coordinates (Not the general scale length like mm or cm)
Option 1: Image Segmenattion
- Do Image segmentation and find the ROI (Dark part of the images)
- Please do some sort of morpho operations to enure having single blob only (Dark region)
- Find the distance between farthermost two black pixels
Oprion 2: Using ginput
data=imread('image9.jpeg');
imshow(data);
[x y]=ginput(6);
x=round(x);
y=round(y);
image1_dist=sqrt((x(2)^2-x(1)^2)+y(2)^2-y(1)^2)
image2_dist=sqrt((x(4)^2-x(3)^2)+y(4)^2-y(3)^2)
image3_dist=sqrt((x(6)^2-x(5)^2)+y(6)^2-y(5)^2)
Command Window:
image1_dist =
300.3681
image2_dist =
331.2990
image3_dist =
337.3603
>>
4 个评论
KALYAN ACHARJYA
2020-6-21
As images number are quite high, then it must be automated to get the distance, see option 1
mathru
2020-6-21
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