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 个评论
Khulood Malek
2020-6-10
Image of cemeraman how to obtain the binary image from the original images and plot it
Image Analyst
2020-6-10
Khulood, if you'll search my Answer below you'll see a variable called binaryImage and how I get it via thresholding.
采纳的回答
Image Analyst
2013-7-17
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!');
0 个评论
更多回答(2 个)
Lokesh Ravindranathan
2013-7-17
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 个评论
Image Analyst
2013-7-17
You don't need to call permute() and reshape() - simply do I(:). But I don't think that's what he wants.
Ali nafaa
2022-11-29
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 个评论
Ali nafaa
2022-11-29
create a new Image Array with the same number of rows and columns as original image array, containing all elements as zero.
Image Analyst
2022-11-29
Yes, that's what your call to zeros() does. But where does the data hiding (embedding) come about in your code?
另请参阅
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