How can I extract the region of interest and its features of the highest moving energy/intensity area
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The following is a part of images (video) that taken in an experiment
How can I only take into consideration the highest moving energy/intensity area that keeps moving and discard the rest of the image?
I mean I want only to extract the region of interest (the highest moving energy/intensity area) and its features?
I have multiple experiments (around 60000) and I want to do the same for all of them
Note: When you run it as a video you will notice the area
Note that the ROI alawys has more events (more density), this will help to avoid annotation process
load ('data.mat')
for i = 1:201
imshow(data(:,:,:,i),[]);
pause(0.001)
end
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Answers (2)
Image Analyst
on 11 Dec 2023
The Computer Vision Toolbox has tracking functions in it. Look into them.
7 Comments
Image Analyst
on 14 Dec 2023
Try this:
% Demo 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 = 16;
markerSize = 20;
%--------------------------------------------------------------------------------------------------------
% READ IN TEST IMAGE
folder = pwd;
baseFileName = "m's image.png";
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 size
[rows, columns, numberOfColorChannels] = size(grayImage)
% Convert to grayscale if it is not already.
if numberOfColorChannels == 3
grayImage = grayImage(:, :, 2);
end
% Get rid of white frame around the image.
allWhiteRows = all(grayImage == 255, 2);
allWhiteColumns = all(grayImage == 255, 1);
grayImage = grayImage(~allWhiteRows, ~allWhiteColumns);
% Display the image.
subplot(2, 2, 1);
imshow(grayImage);
axis('on', 'image');
impixelinfo;
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% Get vertical profile
verticalProfile = sum(grayImage, 2);
% Display the profile.
subplot(2, 2, 3);
plot(verticalProfile, 'b-');
grid on;
% Erase rows with integrated gray levels less than 500 to make sure the blobs are separated.
grayImage(verticalProfile < 500, :) = 0;
%--------------------------------------------------------------------------------------------------------
% Threshold the image.
binaryImage = grayImage >= 1;
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 2, 2);
% imhist(grayImage);
imshow(binaryImage, []);
impixelinfo;
axis('on', 'image');
title('Initial Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
g.Name = 'Demo by Image Analyst';
g.NumberTitle = 'off';
drawnow;
%--------------------------------------------------------------------------------------------------------
% Call a closing to fill in and connect some small blobs.
se = true(3, 15);
binaryImage = imclose(binaryImage, se);
% Take the largest 3 blobs.
binaryImage = bwareafilt(binaryImage, 3);
% Fill holes.
binaryImage = imfill(binaryImage, 'holes');
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
impixelinfo;
axis('on', 'image');
title('Final Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% Get area weighted by shape of outline.
area1 = bwarea(binaryImage)
% Get areas as a simple pixel count.
props = regionprops(binaryImage, 'Area');
area2 = [props.Area]
% Display the original image.
subplot(2, 2, 4);
imshow(grayImage);
axis('on', 'image');
hold on;
% Get the boundary of the mask.
boundaries = bwboundaries(binaryImage);
% Display the outline over the original image.
visboundaries(boundaries, 'Color','r', 'LineWidth',1);
caption = sprintf('Total Area of all %d blobs = %.1f pixels', numel(props), area1)
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
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