MATLAB: How to find the least pixel intensity value for each connected component

digital image processingimage processingImage Processing Toolbox

Binary image:

Green image:

I have a binary image with some pixels as 1 and some as 0 forming a image of group of connected components(white spots within the black image).I need to find the intensities of the pixels of these white spots in other image(green image) and find the pixel with lowest intensity and its value in the green image.I need to find the lowest intensity pixel and its value in the green image for all the white clusters in the binary image.

Can somebody please help me how to find it?

Thank you.

I am enclosing the binary image as finalcandidates,png and the green image as Ig.png.

Best Answer

See demo below. Adapt as needed:

grayImage = imread('coins.png');
subplot(2, 2, 1);
imshow(grayImage);
subplot(2, 2, 2);
histogram(grayImage)
binaryImage = imfill(grayImage > 90, 'holes');
binaryImage = bwareafilt(binaryImage, 10);
subplot(2, 2, 3);
imshow(binaryImage);
subplot(2, 2, 4);
[labeledImage, numBlobs] = bwlabel(binaryImage);
props = regionprops(labeledImage, grayImage, 'PixelValues', 'PixelList')
for k = 1 : numBlobs
    % Fin the min value of this blob's pixel values.
    thisBlobsMin = min(props(k).PixelValues);
    % Get locations in this blob
    mask = ismember(labeledImage, k);
	maskedImage = grayImage .* uint8(mask);
    % Find all the rows and columns where it appears
    [rows, columns] = find(maskedImage == thisBlobsMin);
    imshow(maskedImage);
	axis('on', 'image');
	hold on;
	plot(columns, rows, 'r+', 'LineWidth', 2, 'MarkerSize', 15);
	hold off
	caption = sprintf('Showing cross at %d mins for blob #%d of %d.\n', ...
		length(rows), k, numBlobs);
	title(caption, 'FontSize', 12);
	fprintf('%s\n', caption);
end
fprintf('Done!\n');

Related Solutions

MATLAB: Binary Image – Black region detection

Mohsina, 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 short g;
format compact;
fontSize = 25;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'image1.png';
% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);
%===============================================================================
% Read in a demo image.
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, 2, 1);
imshow(grayImage, []);
axis on;
axis image;
caption = sprintf('Original Gray Scale Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);
% 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.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
drawnow;
% Create binary image of the black blobs from grayscale image.
binaryImage = grayImage == 0;
% Get rid of the background.
binaryImage = imclearborder(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Label the blobs
[labeledImage, numBlobs] = bwlabel(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Let's assign each blob a different color to visually show the user the distinct blobs.
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
% coloredLabels is an RGB image.  We could have applied a colormap instead (but only with R2014b and later)
subplot(2, 2, 3);
imshow(coloredLabels);
axis on;
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
caption = sprintf('Pseudo colored labels, from label2rgb().');
title(caption, 'FontSize', fontSize);
drawnow;
% Make measurements of bounding box.
props = regionprops(labeledImage, 'BoundingBox');
% Display the image.
subplot(2, 2, 4);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image with Boxes', 'FontSize', fontSize, 'Interpreter', 'None');
% Display the bounding boxes around them.
hold on;
for k = 1 : numBlobs
  thisBoundingBox = props(k).BoundingBox
  rectangle('Position', thisBoundingBox, ...
    'EdgeColor', 'c', 'LineWidth', 2);
end

MATLAB: Obtain average image threshold without the background

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 = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.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, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255;  %imbinarize(grayImage);
subplot(2, 2, 2);
imshow(mask, []);
impixelinfo;
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Display histogram of image but only the image within the mask
subplot(2, 3, 4);
histogram(grayImage(mask), 0:255);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))
% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);
% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;
subplot(2, 3, 5);
imshow(brightStuff, []);
impixelinfo;
title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
subplot(2, 3, 6);
darkStuff = ~brightStuff & mask;
imshow(darkStuff, []);
impixelinfo;
title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;

Best Answer

Related Solutions

MATLAB: Binary Image – Black region detection

MATLAB: Obtain average image threshold without the background

Related Question