How to find the area for each regions with different pixels intensity

hi, there. i need your help. I ve this picture and i need to find the area for each of the regions with different pixels value. thank you in advance for those who willing to help me.

Answer 1

[darova]

See this trick

I0 = imread('image.png');
kk = unique(I0(:));
for i = 1:length(kk)
    I1 = I0 == i;
    imshowpair(I0,I1)
    pause(0.5)
end

[Image Analyst]

Almost. To get the pixel counts:

I0 = imread('image.png');
kk = unique(I0(:));
for i = 1:length(kk)
    thisGrayLevel = kk(i)
    I1 = I0 == thisGrayLevel;
    imshowpair(I0, I1)
    pixelCount = nnz(I1);
    caption = sprintf('For Gray Level %d, there are %d pixels.', thisGrayLevel, pixelCount)
    title(caption, 'FontSize', 15);
    pause(0.5)
end

But even that doesn't do it. Do you know why? What if two separate regions have the same gray level? This gives them sum of both of them, not each region's area by itself.

Answer 2

[Image Analyst]

Try this:

grayImage = imread('image.png');
uniqueGrayLevels = unique(grayImage(:))
for k = 1:length(uniqueGrayLevels)
	thisGrayLevel = uniqueGrayLevels(k);
	mask = grayImage == thisGrayLevel;
	imshowpair(grayImage, mask)
	impixelinfo;
	pixelCount = nnz(mask);
	
	% Identify the separate regions' areas.
	props = regionprops(mask, 'Area');
	allAreas = [props.Area];
	caption = sprintf('\nFor Gray Level %d, there are a total of %d pixels in %d regions.', thisGrayLevel, pixelCount, length(allAreas));
	title(caption, 'FontSize', 15);
	for r = 1 : length(allAreas)
		fprintf('  For region %d of graylevel %d, there are %d pixels.\n', r, thisGrayLevel, allAreas(r));
	end
	pause(0.25)
end
uniqueGrayLevels' % Show again in the command window.

[Nauratul Suqda]

first of all . thank you for replying me. here, let me explain. i ve to find the area of pink colour region on the left colomn. i got these 5 pictures(right side) from matlab after implemented bresson model. here the problem is i dont know which one of those images should i used to get the area. would you please tell me which of the images can help me in determining the area of pink colour region?

[Image Analyst]

I never heard of that model. What I would do is use the Color Thresholder on the Apps tab of the tool ribbon. You forgot to attach the original image so I had to get that extremely poor quality image from what you posted, so it looks awful, and not just because it looks like a severed finger from a horrific accident.

% Demo to find pink pixels.
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
fprintf('Beginning to run %s.m ...\n', mfilename);

%-----------------------------------------------------------------------------------------------------------------------------------
% Read in image.
folder = pwd;
baseFileName = 'pink.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
rgbImage = imread(fullFileName);
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the RGB image full size.
subplot(1, 2, 1);
imshow(rgbImage, []);
axis('on', 'image');
caption = sprintf('Original Image : "%s"', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.


% Set up figure properties:
% Enlarge figure to full screen.
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
% 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.
hFig1.Name = 'Demo by Image Analyst';

% Threshold the image to find the small dark black thing.
[mask, maskedRGBImage] = createMask(rgbImage);
% Fill the blobs.
mask = imfill(mask, 'holes');
% Take the largest blob only.
mask = bwareafilt(mask, 1);

% Take the blobs only if they're 400 pixels or larger.
mask = bwareaopen(mask, 400);
% Fill holes
mask = imfill(mask, 'holes');
% Display the binary image.
subplot(1, 2, 2);
imshow(mask, []);
axis('on', 'image');
caption = sprintf(' Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.

% Get the boundary
boundaries = bwboundaries(mask);
boundaries = boundaries{1}; % Extract from cell
x = boundaries(:, 2);
y = boundaries(:, 1);
hold on;
subplot(1, 2, 1);
hold on;
plot(x, y, 'r-', 'LineWidth', 3);

%================================================================================================================================
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.

% Auto-generated by colorThresholder app on 27-Jun-2020
%------------------------------------------------------


% Convert RGB image to chosen color space
I = rgb2hsv(RGB);

% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.963;
channel1Max = 0.139;

% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.441;
channel2Max = 1.000;

% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.356;
channel3Max = 1.000;

% Create mask based on chosen histogram thresholds
sliderBW = ( (I(:,:,1) >= channel1Min) | (I(:,:,1) <= channel1Max) ) & ...
	(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
	(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;

% Initialize output masked image based on input image.
maskedRGBImage = RGB;

% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;

end