MATLAB: How to binarize this image

binarizeimage processingMATLAB and Simulink Student Suite

hi, I have a code :

image=imread('guava.jpg');
figure
imshow(image)
imR1=image(:,:,1);
imG1=image(:,:,2);
imB1=image(:,:,3);
gray = uint8(0.299*double(imR1) + 0.587*double(imG1) + 0.114*double(imB1));
%opening operation
di = strel('line',50,100);
dilate = imdilate(gray,di);
er = strel('line',50,100);
erode = imerode(dilate,er);
%difference image between opening operation and grayscale
difference_image = double(gray) - double(erode);
figure; % Open up another figure window.
subplot (2,2,1)
imshow(dilate)
subplot (2,2,2)
imshow(erode)
subplot(2,2,3)
imshow(difference_image, []); % Display the difference image.
outputImage = uint8(255 * mat2gray(difference_image));
figure
imshow(outputImage)

the result is like :

I need to transform that image into this one :

they said "convert to binary image". I tried with imbinarize and im2bw, the result is all white. what should I do to get that binary image?

Best Answer

The image you show is more like a gray scale image. To get a binary image, do this:

rgbImage = imread('original2.PNG');
binaryImage = rgbImage(:,:,1) < 200;
imshow(binaryImage);

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MATLAB: How to enchant image using histeq

It's a BAD idea to call your image variable "image" because that is the name of a built-in function.

Simply linearly stretch the image with mat2gray():

outputImage = uint8(255 * mat2gray(grayImage));

Histogram equalization gives crummy, unnatural looking images and I always avoid it unless forcefully asked by students who need it for their homework. In the real world I don't think any good image analysts use it because (1) it's not necessary, and (2) it gives lousy looking images.

MATLAB: Extracting black pixels from a specific region of an image and overlaying it on another image

Here's the full demo for you:

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 = 'o4s1_11.bmp';
% Get the full filename, with path prepended.
folder = pwd
fullFileName = fullfile(folder, baseFileName);
%===============================================================================
% Read in a first image.
grayImage1 = 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(grayImage1)
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.

  grayImage1 = grayImage1(:, :, 2); % Take green channel.

end
% Display the image.



subplot(2, 2, 1);
imshow(grayImage1, []);
axis on;
axis image;
caption = sprintf('Image1');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, .96]);
% 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;
%===============================================================================
% Read in a second image.
fullFileName = fullfile(pwd, 'blankv5.bmp');
grayImage2 = 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(grayImage2)
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.
  grayImage2 = grayImage2(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 2, 2);
imshow(grayImage2, []);
axis on;
axis image;
caption = sprintf('Image2');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Display the histogram of the image so we can see what threshold to use.
subplot(2, 2, 3);
histogram(grayImage2);
grid on;
% Binarize the image.
threshold = 128;
binaryImage = grayImage1 < threshold;  % Determine number from histogram.
% Get rid of surround that is touching the border.
binaryImage = imclearborder(binaryImage);
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
axis on;
axis image;
caption = sprintf('Binary Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Use this binary image to transfer the stuff in the second image.
grayImage2(binaryImage) = grayImage1(binaryImage);
% Display the image.
subplot(2, 2, 4);
imshow(grayImage2, []);
axis on;
axis image;
caption = sprintf('Final Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;

Best Answer

Related Solutions

MATLAB: How to enchant image using histeq

MATLAB: Extracting black pixels from a specific region of an image and overlaying it on another image

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