how to convert a grayscale image to binary sequence

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I'm research on watermarking. I want to convert a grayscale image MxN pixel (a pixel value 0~255)in to a binary sequence and permute it to embed this sequence into another image. after i can extract this sequence and restore to original grayscale image. What should i do. Please help me.
  2 Comments
Image Analyst
Image Analyst on 10 Jun 2020
Khulood, if you'll search my Answer below you'll see a variable called binaryImage and how I get it via thresholding.

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Accepted Answer

Image Analyst
Image Analyst on 17 Jul 2013
Here's my LSB watermarking demo:
% Demo to watermark an image by hiding another image in a certain bit
% plane. Sometimes called "LSB Watermarking" or something similar.
% User is asked which bit plane they want to hide the image in.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures.
clear; % Erase all existing variables.
workspace; % Make sure the workspace panel is showing.
fontSize = 12;
% Read in the image what will have another image hidden into it.
baseFileName='moon.tif';
% baseFileName='cameraman.tif';
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
% 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
originalImage = imread(fullFileName);
% Get the number of rows and columns in the original image.
[visibleRows visibleColumns numberOfColorChannels] = size(originalImage);
if numberOfColorChannels > 1
% If it's color, extract the red channel.
originalImage = originalImage(:,:,1);
end
% Display the original gray scale image.
subplot(3, 3, 4);
imshow(originalImage, []);
title('Original Grayscale Starting Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off')
% read the message image you want to hide in the cover image
baseFileName='cameraman.tif';
% baseFileName='moon.tif';
% 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
hiddenImage = imread(fullFileName);
% Get the number of rows and columns in the hidden image.
[hiddenRows hiddenColumns numberOfColorChannels] = size(hiddenImage);
if numberOfColorChannels > 1
% If it's color, extract the red channel.
hiddenImage = hiddenImage(:,:,1);
end
% Display the image.
subplot(3, 3, 1);
imshow(hiddenImage, []);
title('Image to be Hidden', 'FontSize', fontSize);
% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(hiddenImage);
subplot(3, 3, 2);
bar(pixelCount);
title('Histogram of image to be hidden', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
grid on;
thresholdValue = 70;
binaryImage = hiddenImage < thresholdValue;
% Display the image.
subplot(3, 3, 3);
imshow(binaryImage, []);
caption = sprintf('Hidden Image Thresholded at %d', thresholdValue);
title(caption, 'FontSize', fontSize);
% Get the bit plane to hide the image in.
prompt = 'Enter the bit plane you want to hide the image in (1 - 8) ';
dialogTitle = 'Enter Bit Plane to Replace';
numberOfLines = 1;
defaultResponse = {'6'};
bitToSet = str2double(cell2mat(inputdlg(prompt, dialogTitle, numberOfLines, defaultResponse)));
% If image to be hidden is bigger than the original image, scale it down.
if hiddenRows > visibleRows || hiddenColumns > visibleColumns
amountToShrink = min([visibleRows / hiddenRows, visibleColumns / hiddenColumns]);
binaryImage = imresize(binaryImage, amountToShrink);
% Need to update the number of rows and columns.
[hiddenRows hiddenColumns] = size(binaryImage);
end
% Tile the hiddenImage, if it's smaller, so that it will cover the original image.
if hiddenRows < visibleRows || hiddenColumns < visibleColumns
watermark = zeros(size(originalImage), 'uint8');
for column = 1:visibleColumns
for row = 1:visibleRows
watermark(row, column) = binaryImage(mod(row,hiddenRows)+1, mod(column,hiddenColumns)+1);
end
end
% Crop it to the same size as the original image.
watermark = watermark(1:visibleRows, 1:visibleColumns);
else
% Watermark is the same size as the original image.
watermark = binaryImage;
end
% Display the thresholded binary image - the watermark alone.
subplot(3, 3, 5);
imshow(watermark, []);
caption = sprintf('Hidden Image\nto be Inserted into Bit Plane %d', bitToSet);
title(caption, 'FontSize', fontSize);
% Set the bit of originalImage(a copy, actually) to the value of the watermark.
watermarkedImage = originalImage; % Initialize
for column = 1 : visibleColumns
for row = 1 : visibleRows
watermarkedImage(row, column) = bitset(originalImage(row, column), bitToSet, watermark(row, column));
end
end
% Display the image.
subplot(3, 3, 6);
imshow(watermarkedImage, []);
caption = sprintf('Final Watermarked Image\nwithout added Noise');
title(caption, 'FontSize', fontSize);
% add noise to watermarked image
noisyWatermarkedImage = imnoise(watermarkedImage,'gaussian', 0, 0.0005);
% Display the image.
subplot(3, 3, 7);
imshow(noisyWatermarkedImage, []);
caption = sprintf('Watermarked Image\nwith added Noise');
title(caption, 'FontSize', fontSize);
%====================================================================================
% Now let's pretend we are starting with the watermarked noisy corrupted image.
% We want to recover the watermark.
% Use the known bitplane of watermarked image to recover the watermark.
recoveredWatermark = zeros(size(noisyWatermarkedImage));
recoveredNoisyWatermark = zeros(size(noisyWatermarkedImage));
for column = 1:visibleColumns
for row = 1:visibleRows
recoveredWatermark(row, column) = bitget(watermarkedImage(row, column), bitToSet);
recoveredNoisyWatermark(row, column) = bitget(noisyWatermarkedImage(row, column), bitToSet);
end
end
% Scale the recovered watermark to 0=255
recoveredWatermark = uint8(255 * recoveredWatermark);
recoveredNoisyWatermark = uint8(255 * recoveredNoisyWatermark);
% Display the images.
subplot(3, 3, 8);
imshow(recoveredWatermark, []);
caption = sprintf('Watermark Recovered\nfrom Bit Plane %d of\nNoise-Free Watermarked Image', bitToSet);
title(caption, 'FontSize', fontSize);
% Display the images.
subplot(3, 3, 9);
imshow(recoveredNoisyWatermark, []);
caption = sprintf('Watermark Recovered\nfrom Bit Plane %d of\nNoisy Watermarked Image', bitToSet);
title(caption, 'FontSize', fontSize);
msgbox('Done with demo!');

More Answers (2)

Lokesh Ravindranathan
Lokesh Ravindranathan on 17 Jul 2013
For converting image into binary sequence,
For permutation use the following code
permute(reshape(I, numel(I), 1))
Use the permuted image for embedding.
  1 Comment
Image Analyst
Image Analyst on 17 Jul 2013
You don't need to call permute() and reshape() - simply do I(:). But I don't think that's what he wants.

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Ali nafaa
Ali nafaa on 29 Nov 2022 at 17:25
x = imread('cameraman.tif');
figure,imshow(x);
[r,c] = size (x);
output=zeros(r,c);
for i = 1 : r
for j = 1 : c
if x(i,j) > 128
output(i,j)=1;
else
output(i,j)=0;
end
end
end
figure,imshow(output);
  3 Comments
Image Analyst
Image Analyst on 29 Nov 2022 at 18:54
Yes, that's what your call to zeros() does. But where does the data hiding (embedding) come about in your code?

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