MATLAB: How to divide an image at its intensity level??? one part of the histogram is before the mean of image and the other part after the mean of the image

image processingImage Processing Toolboximage segmentation

sir, i want to write a program which separates an image into two parts at its intensity level.one part of the histogram is below the mean of the image and the second part should be after the mean of image and these two parts of histogram of the image should be separately plotted.

Best Answer

threshold = mean2(grayScaleImage); % or whatever intensity you want.
binaryImage = grayScaleImage > threshold;
image1 = grayScaleImage; % Initialize

image1(binaryImage) = 0;
imshow(image1);
image2 = grayScaleImage; % Initialize
image2(~binaryImage) = 0;
imshow(image2);

See attached full blown demo, in blue text below.

Related Solutions

MATLAB: Integers can only be combined with integers of the same class, or scalar doubles

You have to case "Image" as double in

Threshold= conv2(Image, AverageMask);

By the way, don't use "Image" as a variable name since it's so close to the built-in function called "image" and you risk using the wrong one with a simple typo. There were a number of other errors in there, which I fixed for you:

clc;  % Clear command window.
clear;  % Delete all variables.
close all;  % Close all figure windows except those created by imtool.
imtool close all;  % Close all figure windows created by imtool.
workspace;  % Make sure the workspace panel is showing.
fontSize = 16;
% Global Thresholding of an unsuitable image. In comparison, the same
% image is thresholded in an Adaptive manner.
grayImage= imread('cameraman.tif');
clear ball;
% Display the original image (normalized to the range 0-64)
colormap(gray);
subplot(2, 2, 1); 
% Reduce the contrast.
imshow(round(grayImage/4));
title('(a) The Original image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
subplot(2, 2, 2); 
bar(pixelCount);
grid on;
title('(b) Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
% Perform Global thresholding with a threshold of 130
Tg= 130;
GlobalThresholded = grayImage > Tg;
colormap(gray);
subplot(2, 2, 3); 
imshow(GlobalThresholded);
title('(c) Globally Thresholded image, Tg=130', 'FontSize', fontSize);
% Perform an Adaptive Thresholding: average over a neighborhood of 61x61
AverageMask= ones(61, 61) / (61^2);
Threshold = conv2(double(grayImage), AverageMask, 'same');
% Get the image that is 6 above the deviation from the local mean.
ThresholdMask = double(grayImage) - Threshold + 6;  % Why 6????
AdaptiveThresholded = ThresholdMask > 0;
subplot(2, 2, 4); 
imshow(AdaptiveThresholded);
title('(d) Adaptive Thresholded Image', 'FontSize', fontSize);

By the way, do you know that CLAHE is implemented by MATLAB's Image Processing Toolbox. You can use the function adapthisteq() to do essentially what you tried to, and do a better job of it.

MATLAB: How the Peak value of the image histogram can be obtaind

[pixelCounts, grayLevels] = imhist(grayImage);
[maxCount, indexOfMax] = max(pixelCounts);
grayLevelAtMax = grayLevels(indexOfMax);

Best Answer

Related Solutions

MATLAB: Integers can only be combined with integers of the same class, or scalar doubles

MATLAB: How the Peak value of the image histogram can be obtaind

Related Question