Conversion of grayscale to binary Image

when a dataset containing gray scale images are converted to binary images , few images are getting complemented i.e, few images with black as background and few with white as background.
I want all images to be in a uniform way, black background and white foreground.
how to use imcomplement() for selected images in a datasset? or is there anyother way?
i have attached few sample input and their corresponding binary images from the dataset.
Thankyou in advance

 Accepted Answer

There is an option for that in imbinarize to make sure you always get either the brighter thing or the darker thing:
BW = imbinarize(grayImage,'adaptive','ForegroundPolarity','dark','Sensitivity',0.4);

8 Comments

Thankyou sir for the response
but when i apply this command, segmentation of lung doesnt happen properly.
i have used the same code given by you for the segmentation.
i have attached the images.
Attach the original gray scale images, not screenshots of binary images, and your program
yes,sir,may be use
clc; clear all; close all;
grayImage = imread('https://ww2.mathworks.cn/matlabcentral/answers/uploaded_files/864875/CHNCXR_0639_1-input.png');
if ndims(grayImage) == 3
grayImage = rgb2gray(grayImage);
end
BW = ~imbinarize(grayImage,'adaptive','ForegroundPolarity','dark','Sensitivity',0.55);
figure; imshow(BW, []);
I have attached the code and grayImage sir.
folder = pwd; % 'E:\project\dataset'
fullFileName = fullfile(folder, 'CHNCXR_0639_1-input.jpg');
rgbImage=imread(fullFileName);
[rows, columns, numberOfColorChannels] = size(rgbImage)
subplot(2, 2, 1);
imshow(rgbImage);
axis('on', 'image')
title('Original RGB image')
% Convert to gray scale.
if numberOfColorChannels == 3
grayImage = rgb2gray(rgbImage);
else
% It's already gray scale.
grayImage = rgbImage;
end
% Resize.
grayImage = imresize(grayImage,[256,256]);
subplot(2, 2, 2);
imshow(grayImage);
axis('on', 'image')
title('Resized gray scale image')
% Binarize
binaryImage = imbinarize(grayImage,'adaptive','ForegroundPolarity','dark','Sensitivity',0.4);
subplot(2, 2, 3);
imshow(binaryImage);
binaryImage = imclearborder(binaryImage);
binaryImage = bwareafilt(binaryImage,2);
subplot(2, 2, 3);
imshow(binaryImage);
axis('on', 'image')
title('Lungs Only')
% Initialization Steps.
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 = 16;
folder = pwd; % 'E:\project\dataset'
fullFileName = fullfile(folder, 'CHNCXR_0639_1-input.png');
rgbImage=imread(fullFileName);
[rows, columns, numberOfColorChannels] = size(rgbImage)
subplot(2, 3, 1);
imshow(rgbImage);
axis('on', 'image')
title('Original RGB image', 'FontSize', fontSize)
impixelinfo;
% Convert to gray scale.
if numberOfColorChannels == 3
grayImage = rgb2gray(rgbImage);
else
% It's already gray scale.
grayImage = rgbImage;
end
subplot(2, 3, 2);
imhist(grayImage);
grid on;
title('Histogram of gray scale image', 'FontSize', fontSize)
% Resize.
grayImage = imresize(grayImage,[256,256]);
subplot(2, 3, 3);
imshow(grayImage);
axis('on', 'image')
title('Resized gray scale image', 'FontSize', fontSize)
% Binarize
% Determine threshold
lowThreshold = 0;
highThreshold = 189;
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage);
binaryImage = grayImage >= lowThreshold & grayImage <= highThreshold;
% binaryImage = imbinarize(grayImage,'adaptive','ForegroundPolarity','dark','Sensitivity',0.4);
% binaryImage = imbinarize(grayImage);
subplot(2, 3, 4);
imshow(binaryImage);
title('Binary Image', 'FontSize', fontSize)
binaryImage = imclearborder(binaryImage);
binaryImage = bwareafilt(binaryImage,2);
binaryImage = bwconvhull(binaryImage, 'objects');
subplot(2, 3, 5);
imshow(binaryImage);
axis('on', 'image')
title('Lungs Only', 'FontSize', fontSize)
% Plot the borders of all the blobs in the overlay above the original grayscale image
% using the coordinates returned by bwboundaries().
% bwboundaries() returns a cell array, where each cell contains the row/column coordinates for an object in the image.
subplot(2, 3, 6);
imshow(grayImage); % Optional : show the original image again. Or you can leave the binary image showing if you want.
% Here is where we actually get the boundaries for each blob.
boundaries = bwboundaries(binaryImage);
% boundaries is a cell array - one cell for each blob.
% In each cell is an N-by-2 list of coordinates in a (row, column) format. Note: NOT (x,y).
% Column 1 is rows, or y. Column 2 is columns, or x.
numberOfBoundaries = size(boundaries, 1); % Count the boundaries so we can use it in our for loop
% Here is where we actually plot the boundaries of each blob in the overlay.
hold on; % Don't let boundaries blow away the displayed image.
for k = 1 : numberOfBoundaries
thisBoundary = boundaries{k}; % Get boundary for this specific blob.
x = thisBoundary(:,2); % Column 2 is the columns, which is x.
y = thisBoundary(:,1); % Column 1 is the rows, which is y.
plot(x, y, 'r-', 'LineWidth', 2); % Plot boundary in red.
end
hold off;
caption = sprintf('%d Outlines, from bwboundaries()', numberOfBoundaries);
fontSize = 15;
title(caption, 'FontSize', fontSize);
axis('on', 'image'); % Make sure image is not artificially stretched because of screen's aspect ratio.
If you want the shape to better hug/follow the binary image, instead of using the convex hull, you could fill the blobs and use activecontour. See attached demo.
ANUSHA H P
ANUSHA H P on 21 Jan 2022
Edited: ANUSHA H P on 21 Jan 2022
yes sir, it was of grt help ,thankyou.

Sign in to comment.

More Answers (0)

Asked:

on 17 Jan 2022

Edited:

on 21 Jan 2022

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!