watermarking

can anyone please tell me how to code the following algorithm:

1) Select a set of  P pixels from I where L is to be embedded, and call  p as a  watermarking area.

2) Denote the set of pixels corresponding to P in w by Q.

3) For each pixel X with value p in P , denote the corresponding pixel in Q as and  the value of the corresponding pixel Y in L as , and conduct the following steps.

a) Apply an estimation technique to derive to be a value close to P , using the values of the neighboring pixels of  X(excluding itself).
b) Set b to be the value l.
c) Map  p  to a new value  q=Fb-1(Fa(p).
d) Set the value of Z to be q.

4) Set the value of each remaining pixel in W, which is outside the region P, to be equal to that of the corresponding pixel in I.

[Walter Roberson]

What is "w" in 2) ? What are Fa and Fb in 3(c) ?

[Image Analyst]

The whole thing is an alphabet soup of random letters. Continuing on, what is (capital) W? What is Z? What is b in step 3b? Why are you changing the values of BOTH the Z image (in step 3d) AND the W image (in step 4)? Are there two output images?

[Sneha]

w is the watermarked image that i need as output after embedding watermark L on Image I. Fa=(p-a)mod 256 and Fb inverse = Fa(p)+b, where b are the pixel values of watermark image or L(here) |Z is the value,that is denoted to the region of image after the transformation,like d watermaked area. and no there are no 2 outputs..

[Image Analyst]

Doesn't look like it should be that hard at all. Did you try anything at all? Let's see your code/homework answer. I can give you a masking demo if you want, but you should be able to do the simple image arithmetic yourself, shouldn't you?

[Sneha]

Actually im new to matlab,so still in the process of learning it.It will be really helpful if u can provide me the masking demo of the code.

[Image Analyst]

See demo below.

Answer 1

[Image Analyst]

Are you looking for help as to how to select the area? How about rbbox, roipoly, roipolyold, imfreehand, imrect, or imellipse? Get a binary image representing the region you drew, then say

I(binaryImage) = I(binaryImage) - L(binaryImage);

if I'm interpreting your "q" formula correctly, or something like that.

Answer 2

[Image Analyst]

% Demo to have the user freehand draw an irregular shape over
% a gray scale image, have it extract only that part to a new image,
% and to calculate the mean intensity value of the image within that shape.
% By ImageAnalyst
%

% Change the current folder to the folder of this m-file.
if(~isdeployed)
  cd(fileparts(which(mfilename)));
end
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;

% Read in standard MATLAB gray scale demo image.
grayImage = imread('cameraman.tif');
subplot(2, 3, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish');
uiwait(msgbox(message));
hFH = imfreehand();

% Create a binary image ("mask") from the ROI object.
binaryImage = hFH.createMask();
% Display the freehand mask.
subplot(2, 3, 2);
imshow(binaryImage);
title('Binary mask of the region', 'FontSize', fontSize);

% Calculate the area, in pixels, that they drew.
numberOfPixels1 = sum(binaryImage(:))
% Another way to calculate it that takes fractional pixels into account.
numberOfPixels2 = bwarea(binaryImage)

% Get coordinates of the boundary of the freehand drawn region.
structBoundaries = bwboundaries(binaryImage);
xy=structBoundaries{1}; % Get n by 2 array of x,y coordinates.
x = xy(:, 2); % Columns.
y = xy(:, 1); % Rows.
subplot(2, 3, 1); % Plot over original image.
hold on; % Don't blow away the image.
plot(x, y, 'LineWidth', 2);
drawnow; % Force it to draw immediately.

% Burn line into image by setting it to 255 wherever the mask is true.
burnedImage = grayImage;
burnedImage(binaryImage) = 255;
% Display the image with the mask "burned in."
subplot(2, 3, 3);
imshow(burnedImage);
caption = sprintf('New image with\nmask burned into image');
title(caption, 'FontSize', fontSize);
% Mask the image and display it.
% Will keep only the part of the image that's inside the mask, zero outside mask.
blackMaskedImage = grayImage;
blackMaskedImage(~binaryImage) = 0;
subplot(2, 3, 4);
imshow(blackMaskedImage);
title('Masked Outside Region', 'FontSize', fontSize);
% Calculate the mean
meanGL = mean(blackMaskedImage(binaryImage));
% Report results.
message = sprintf('Mean value within drawn area = %.3f\nNumber of pixels = %d\nArea in pixels = %.2f', ...
meanGL, numberOfPixels1, numberOfPixels2);
msgbox(message);

% Now do the same but blacken inside the region.
insideMasked = grayImage;
insideMasked(binaryImage) = 0;
subplot(2, 3, 5);
imshow(insideMasked);
title('Masked Inside Region', 'FontSize', fontSize);

% Now crop the image.
topLine = min(x);
bottomLine = max(x);
leftColumn = min(y);
rightColumn = max(y);
width = bottomLine - topLine + 1;
height = rightColumn - leftColumn + 1;
croppedImage = imcrop(blackMaskedImage, [topLine, leftColumn, width, height]);
% Display cropped image.
subplot(2, 3, 6);
imshow(croppedImage);
title('Cropped Image', 'FontSize', fontSize);