MATLAB: How to threshold the image automatically based on its energy content

histogramimage processingthresholding

Say my threshold is taking in those components that constitute about 75% of energy of image and making the remaining as zero.How do I do that?

Best Answer

D_coder, try this:

clc;    % Clear the command window.
clearvars;
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
grayImage = imread('cameraman.tif');
subplot(2, 2, 1);
imshow(grayImage);
title('Original Image', 'FontSize', fontSize);
sortedGrayLevels = double(sort(grayImage(:), 'descend'));
% Sum up the energy from most energetic to least energy.
percentage = cumsum(sortedGrayLevels);
percentage = percentage / percentage(end);
subplot(2, 2, 2);
plot(percentage, 'b-', 'LineWidth', 2);
grid on;
title('Cumulative Distribution Function', 'FontSize', fontSize);
% Find the brighter 75%
% Find the gray level where 75 percent is

index75 = find(percentage >= 0.75, 1, 'first')
grayLevel75 = grayImage(index75)
% threshold the most energy 75%

binaryImage = grayImage > grayLevel75;
subplot(2, 2, 3);
imshow(binaryImage);
title('Brighter 75%', 'FontSize', fontSize);
% Find the darker 75%
% Find the gray level where 75 percent is
index75 = find(percentage >= 0.25, 1, 'first')
grayLevel25 = grayImage(index75)
% threshold the most energy 75%
binaryImage25 = grayImage < grayLevel25;
subplot(2, 2, 4);
imshow(binaryImage25);
title('Darker 75%', 'FontSize', fontSize);

Each binary image will contain 75% of the energy. It just depends if you wanted to start with the darker pixels and work brighter, or start with the brightest pixels and work darker.

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MATLAB: How to get gray color

Try using gray levels instead of the 0-1 range. (It's inconsistent, I know)

grayImage = imread('cameraman.tif');
subplot(2, 2, 1);
imshow(grayImage);
title('Original Image', 'fontSize', fontSize);
drawnow;
grayImg = insertShape(grayImage, 'line', [270 20 30 200], ...
  'LineWidth', 10, 'Color', [0.75 0.75 0.75]*255 ); 
subplot(2, 2, 2);
imshow(grayImg);
impixelinfo;

MATLAB: How to get those object and turn background color into white of the binary image

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 = 20;
% Check that user has the Image Processing Toolbox installed.
hasIPT = license('test', 'image_toolbox');
if ~hasIPT
  % User does not have the toolbox installed.
  message = sprintf('Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?');
  reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes');
  if strcmpi(reply, 'No')
    % User said No, so exit.
    return;
  end
end
% Read in a demo image.
folder = pwd % or wherever the image lives
baseFileName = 'batik22.PNG';
%===============================================================================
% Read in a color reference image.
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 2, 1);
imshow(rgbImage);
title('Original Color Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
% Take the red channel
grayImage = rgbImage(:,:, 1);
subplot(2, 2, 2);
imshow(grayImage);
axis on;
title('Red Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Threshold the image
binaryImage = grayImage < 127;
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Take the 8 largest blobs, then invert the image
binaryImage = ~bwareafilt(binaryImage, 8);
subplot(2, 2, 4);
imshow(binaryImage, []);
caption = sprintf('Final Binary Image with 8 largest blobs');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

Best Answer

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