Calculate intensity of bright and dark blobs in the image

In the attached image, I want to calculate the average intensity of the bright blobs as well as the dark blobs inside the bright blobs.

For example, in this image, there are 8 bright blobs. In top row, third from the left blob, there are 4 dark spots. I need to calculate the average intensity of the 8 bright blobs along with the average intensity of the dark spots inside those bright blobs.

Any help would be appreciated.

Answer 1

[Image Analyst]

See my Image Segmentation Tutorial in my File Exchange:

Image Analyst's File Exchange

It's a generic, general purpose demo of how to threshold an image to find blobs, and then measure things about the blobs, and extract certain blobs based on their areas or diameters.

If you have any more questions, then attach your image HERE (not some third party web site that we can't even get to) with the paperclip icon after you read this:

TUTORIAL: How to ask a question (on Answers) and get a fast answer

Basically

mask = grayImage > someThresholdValue;
mask = bwareafilt(mask, 8); % Take 8 largest.
meanBrightIntensity = mean(grayImage(mask))

Similar for dark blobs:

mask = grayImage < someDarkThresholdValue;
mask = bwareafilt(mask, 4); % Take 4 largest.
meanDarkIntensity = mean(grayImage(mask))

If you want to interactively/visually select the threshold, see my thresholding utility:

https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle

Answer 2

[Image Analyst]

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 = 18;
markerSize = 40;
%--------------------------------------------------------------------------------------------------------
%    READ IN TEST IMAGE
folder = pwd;
baseFileName = 'Image009_ch00_SV.jpg';
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);
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
axis('on', 'image');
title('Green Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% 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.
    fprintf('It is not really gray scale like we expected - it is color\n');
    % Extract the max channel.
    % grayImage = max(grayImage, [], 3);
    % Extract the green channel.
    grayImage = grayImage(:, :, 2);
end

%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 2, 2);
imshow(grayImage, []);
impixelinfo;
axis('on', 'image');
title('Green Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
drawnow;

%--------------------------------------------------------------------------------------------------------
% Threshold to create mask of the bright spots
lowThreshold = 31;
highThreshold = 255;
% Interactively and visually set a threshold on a gray scale image.
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage)
brightMask = grayImage >= lowThreshold & grayImage <= highThreshold;
% Take the largest 8 blobs only.
brightMask = bwareafilt(brightMask, 8);
subplot(2, 2, 3);
imshow(brightMask);
impixelinfo;
axis('on', 'image');
title('Bright Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Get the mean gray level.
meanBrightGrayLevel = mean(grayImage(brightMask));
caption = sprintf('Mean of bright areas = %.1f gray levels.', meanBrightGrayLevel)
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

%--------------------------------------------------------------------------------------------------------
% Get the convex hull of hte bright blobs so we can restrict the dark areas to within the bright areas.
brightMask = bwconvhull(brightMask, "objects");
grayImage(~brightMask) = 0; % Erase outside of the bright areas.

%--------------------------------------------------------------------------------------------------------
% Threshold to create mask of the dark spots
lowThreshold = 18;
highThreshold = 26;
% Interactively and visually set a threshold on a gray scale image.
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage)
darkMask = grayImage >= lowThreshold & grayImage <= highThreshold;
% Take the largest 4 blobs only.
darkMask = bwareafilt(darkMask, 4);
% Fill any holes inside the dark blobs.
darkMask = imfill(darkMask, 'holes');
subplot(2, 2, 4);
imshow(darkMask);
impixelinfo;
axis('on', 'image');
title('Dark Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Get the mean gray level.
meanDarkGrayLevel = mean(grayImage(darkMask));;
caption = sprintf('Mean of dark areas = %.1f gray levels.', meanDarkGrayLevel)
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

It will require adaptation of course.

[Himanshu Mishra]

Thanks a lot. This is excellent.

However, what I am looking for is average intensity of 1 bright blob + average intensity of dark spots inside it (Individually for each bright blob). I am sorry if it was not conveyed properly in the main question. I am not sure if it is even possible. Thanks for all the help anyway.

[Image Analyst]

That's as much as I could do in 5 minutes. Can't you finish it? I'll be traveling and working for the next several hours.

[Himanshu Mishra]

I had actually reached this point using your image segmentation tutorial. The next step is where I am stuck. How to individually count the blobs and the dark spots inside them. You have indeed helped a lot. I will keep trying. Thanks.

[Image Analyst]

Well since you said there were 8 and 4, I extracted exactly that many blobs. If there is some variable number, then you might want to change bwareafilt to give it some size range of valid blob areas. Then it could find however many there are instead of some fixed number.

You can also use bwareaopen to throw out blobs smaller than a certain number of pixels in area. What is the smallest genuine blob you want to consider?