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Generic Lossless Watermarking Project report 2012

1. INTRODUCTION

Digital watermarking is defined as a process of embedding data (watermark) into a

multimedia object to help to protect the owner's right to that object. The embedded data

(watermark) may be either visible or invisible.

The rapid growth in the digital technology, image processing and Internet has made the

reproduction of digitally created information simple and easy. The advancement in World Wide

Web, MMS communication has made it possible to transmit and distribute this digitally created

information in a fast and easy manner without any quality degradation. This new trend has

several advantages which includes flexibility, cost effectiveness, etc., but at the same time, also

possess some serious drawbacks. It allows hackers to manipulate / duplicate / access

information illegally without the owners knowledge. This has created a great concern on

digital content security and is being studied seriously by several academicians and researchers.

In response to these challenges, digital watermarking schemes have been proposed in the last

decade, where a small amount of imperceptible secret information is embedded into the digital

content, which can be extracted at a later stage for copyright assertion, copy control,

broadcasting, authentication, content integrity verification, etc.

Digital watermarking has been investigated deeply for its technical and commercial

feasibility in all media types like, digital photographic image, audio, printed materials or

compound document images, video, etc. It is a proven method for reducing content piracy and

improving the ability to identify, tract and manage digital media. It is widely used in

applications of rights management, remote triggering, filtering/classification, e-commerce, etc.

It is a technique that is used to balance the need for content security with best possibleconsumer experience to enable media and entertainment industries to adapt the advanced

facilities of the modern digital revolution while reducing the threat of content theft.

In watermarking is defined as a technique which embeds data into digital contents such

as text, still images, video and audio data without degrading the overall quality of the digital

media. A watermark is the information to be hidden and also indicates that the hidden

information is transparent, while the term cover media indicates the media used for carrying thewatermark. The watermarked data is the media which contains the watermark. In digital

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watermarking technology, the phrase embedding and extraction means the procedures used for

inserting the watermark into the cover media and extracting the embedded watermark from the

watermarked data respectively. Detection is an important process that is used for detecting

whether the given media containing a particular watermark.

In visible watermarking of images, a secondary image (the watermark) is embedded in

a primary (host) image such that watermark is intentionally perceptible to a human observer

whereas in the case of invisible watermarking the embedded data is not perceptible, but may be

extracted detected by a computer program.

Some of the desired characteristics of visible watermarks are listed below.

A visible watermark should be obvious in both colour and monochrome images.

The watermark should be spread in a large or important area of the image in order toprevent its deletion by clipping.

The watermark should be visible yet must not significantly obscure the image detailsbeneath it.

The watermark must be difficult to remove; removing a watermark should be morecostly and labour intensive thanpurchasing the image from the owner.

The watermark should be applied automatically with little human intervention andlabour.

There are very few visible watermarking techniques available in current literature. The IBM

digital library organization has used a visible watermarking technique to mark the digitized

pages of manuscript from the Vatican archive. Kankanhalli et have proposed a visible

watermarking technique in DCT domain. They divide the image into different blocks, classify

the blocks by perceptual methods proposed in and modify the DCT coefficients of host image

as follows.

(1)

The and coefficients are for block n. The (n) are the DCT coefficients of the

host image block and the DCT coefficients of the watermark image block. In this paper,

we propose a visible watermarking technique that modifies the DCT coefficients of the host

image using equation (l) But, the and values are found out using a mathematical model


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developed by exploiting the texture sensitivity of the human visual system (HVS). This ensures

that the perceptual quality of the image is better preserved. We call scaling factor and as

the embedding factor. We have also proposed a modification to make the watermark more

robust.Several types of watermarking schemes have been proposed for handling different

applications. Examples include

(1). Copyright-related applications where the embedded watermark are robust

(2). Medical, forensic, and intelligence or military applications where the watermark areusually fragile or semi-fragile

(3). Content authentication applications where any tiny changes to the content are notacceptable, the embedding distortion has to be compensated for perfectly.

Digital watermarking techniques originally focused on copyright protection, but have

been exploited in wide range of applications. There are several categories of watermarking

schemes that are designed for different applications. Among them, robust watermarks are

generally used for copyright protection and ownership identification because they are designed

to withstand attacks such as common image processing operations. In contrast, fragile or semi-fragile watermarks are mainly applied to content authentication and integrity attestation

because they are fragile to attacks, i.e., it can detect any changes in an image as well as

localizing the areas that have been changed. Both these techniques are to be treated separately

and this paper deals with content based watermarking system for authentication.


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2. The Discrete Cosine Transform

Like other transforms, the Discrete Cosine Transform (DCT) attempts to decorrelate the

image data. After decorrelation each transform coefficient can be encoded independently

without losing compression efficiency. This section describes the DCT and some of its

important properties.

2.1. The One-Dimensional DCT

The most common DCT definition of a 1-D sequence of length N is

Foru = 0,1,2,,N 1. Similarly, the inverse transformation is defined as

The average value of the sample sequence. In literature, this value is referred to as the

DC Coefficient. All other transform coefficients are called the AC Coefficients. N = 8 andvarying values ofu is shown in Figure. In accordance with our previous observation, the first

the top-left waveform (u = 0) renders a constant (DC) value, whereas, all other waveforms (u =

1, 2,, 7 ) give waveforms at progressively increasing frequencies These waveforms are called

the cosine basis function. Note that these basis functions are orthogonal. Hence, multiplication

of any waveform in Figure 3 with another waveform followed by a summation over all sample

points yields a zero (scalar) value, whereas multiplication of any waveform in Figure 3 with

itself followed by a summation yields a constant (scalar) value. Orthogonal waveforms are


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independent, that is, none of the basis functions can be represented as a combination of other

basis functions.

Fig 2.1 One dimensional cosine basis function (N=8).

If the input sequence has more than Nsample points then it can be divided into sub-

sequences of length Nand DCT can be applied to these chunks independently. Here, a very

important point to note is that in each such computation the values of the basis function points

will not change. Only the values off (x) will change in each sub-sequence. This is a very

important property, since it shows that the basis functions can be pre-computed offline and then

multiplied with the sub-sequences. This reduces the number of mathematical operations (i.e.,

multiplications and additions) thereby rendering computation efficiency.

2.2 The Two-Dimensional DCT

The objective of this document is to study the efficacy of DCT on images. This necessitates the

extension of ideas presented in the last section to a two-dimensional space. The 2-D DCT is a

direct extension of the 1-D case and is given by


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for u,v = 0,1,2,,N 1 and (u) and (v) are defined in (3). The inverse transform is

defined as

for x,y = 0,1,2,,N 1. The 2-D basis functions can be generated by multiplying the

horizontally oriented 1-D basis functions (shown in Figure) with vertically oriented set of the

same functions. The basis functions for N = 8 are shown in. Again, it can be noted that the

basis functions exhibit a progressive increase in frequency both in the vertical and horizontal

direction. The top left basis function of results from multiplication of the DC component in

Figure with its transpose. Hence, this function assumes a constant value and is referred to as the

DC coefficient.

Fig 2.2 Two dimensional DCT basis functions (N = 8). Neutral gray represents zero,

white represents positive amplitudes, and black represents negative amplitude


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3. INTRODUCTION TO MATLAB

What is MATLAB?

MATLAB (MATrix LABoratory) is a tool for numerical computation and visualization. The

basic data element is a matrix, so if you need a program that manipulates array-based data it isgenerally fast to write and run in MATLAB.

Using MATLAB

The Beginning

When you start MATLAB, the command prompt >> appears. You will tell MATLAB what

to do by typing commands at the prompt.

Creating matrices

The basic data element in MATLAB is a matrix. A scalar in MATLAB is a 1x1 matrix, and a

vector is a 1xn (or nx1) matrix.

For example, create a 3x3 matrix A that has 1s in the first row, 2s in the second row, and 3s

in the third row:

>> A = [1 1 1; 2 2 2; 3 3 3]

The semicolon is used here to separate rows in the matrix. MATLAB gives you:

A =

1 1 1

2 2 2

3 3 3

If you dont want MATLAB to display the result of a command, put a semicolon at the end:

>> A = [1 1 1; 2 2 2; 3 3 3];

Matrix A has been created but MATLAB doesnt display it. The semicolon is necessary when

youre running long scripts and dont want everything written out to the screen! Suppose you

want to access a particular element of matrix A:

>> A(1,2)

ans =

1

Suppose you want to access a particular row of A:

>> A(2,:)

ans =

2 2 2


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The : operator you have just used generates equally spaced vectors. You can use it to specify

a range of values to access in the matrix:

>> A(2,1:2)

ans =

2 2

You can also use it to create a vector:

>> y = 1:3

y =

1 2 3

The default increment is 1, but you can specify the increment to be something else:

>> y = 1:2:6

y =

1 3 5

Here, the value of each vector element has been increased by 2, starting from 1, while less than

6.

You can easily concatenate vectors and matrices in MATLAB:

>> [y, A(2,:)]

ans =

1 3 5 2 2 2

You can also easily delete matrix elements. Suppose you want to delete the 2nd element of the

vector y:

>> y(2) = []

y =

1 5

MATLAB has several built-in matrices that can be useful. For example, zeros(n,n) makes an

nxn matrix of zeros.

>> B = zeros(2,2)

B =

0 0

0 0

A few other useful matrices are:

zeros create a matrix of zeros

ones create a matrix of onesrand create a matrix of random numbers


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eye create an identity matrix

Matrix operations

An important thing to remember is that since MATLAB is matrix-based, the multiplication

operator * denotes matrix multiplication. Therefore, A*B is notthe same as multiplying each

of the elements of A times the elements of B. However, youll probably find that at some point

you want to do element-wise operations (array operations). In MATLAB you denote an array

operator by playing a period in front of the operator. The difference between * and .* is

demonstrated in this example:

>> A = [1 1 1; 2 2 2; 3 3 3];

>> B = ones(3,3);

>> A*B

ans =

3 3 3

6 6 6

9 9 9

>> A.*B

ans =

1 1 1

2 2 2

3 3 3

Other than the bit about matrix vs. array multiplication, the basic arithmetic operators in

MATLAB work pretty much as youd expect. You can add (+), subtract (-), multiply (*), divide

(/), and raise to some power (^).

MATLAB provides many useful functions for working with matrices. It also has many scalar

functions that will work element-wise on matrices (e.g., the function sqrt(x) will take the square

root of each element of the matrix x).

Useful matrix functions:

A transpose of matrix A. Also transpose(A).

det(A) determinant of A

eig(A) eigenvalues and eigenvectors

inv(A) inverse of A

svd(A) singular value decomposition

norm(A) matrix or vector norm


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find(A) find indices of elements that are nonzero. Can also pass an expression to this

function, e.g. find(A > 1)finds the indices of elements of A greater than 1.

A few useful math functions:

sqrt(x) square root

sin(x) sine function.

cos(x) - cosine function.

tan(x) - tan function.

exp(x) exponential

log(x) natural log

log10(x) common log

abs(x) absolute value

mod(x) modulus

factorial(x) factorial function

floor(x) round down.

ceil(x)- rounds up

round(x)- round to nearest integer

min(x) minimum elements of an array.

max(x) maximum elements of an array.

M-files and functions

If you are doing a computation of any significant length in MATLAB, you will probably want

to make an m-file. Anything that you would type at the command prompt you can put in the m-

file (for example, script.m) and then run it all at once (by typing the name of the m-file, e.g.

script, at the command prompt). You can even add comments to your m-file, by putting a

% at the beginning of a comment line. You can also use m-files to create your own functions.

For example, suppose you want to make a function that increments the value of each element of

a matrix by some constant. And suppose you want to call the function incrementor. You

would make an m-file called incrementor.m containing the following:

function f = incrementor(x,c)

% Incrementor adds c to each element in the matrix x.

f = x + c;

When you pass a matrix x and value c to this function, the value of f = x+c is returned.You can now call this function from the command line or in another m-file.


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>> incrementor(A,1)

ans =

2 2 2

3 3 3

4 4 4

MATLAB provides several flow control statements that you can use in scripts. These

include:

FOR loops:

for i = 1:10

a(i) = 2;

end

WHILE loops:

while a(i) ~= 0

b(i) = 1/a(i);

end

IF/ELSE statements:

if i > 0

a(i) = 1;

else

a(i) = 0;

end

The break statement can be used to exit from the current FOR or WHILE loop. You may find

it useful at some point in a script to return control to the keyboard, to examine variables or

execute commands. Whenever the command keyboard is encountered in a script, MATLAB

will return control to the keyboard. To return to the script, just type return. MATLAB can

also prompt the user for input during a script. This is done with the input command:

x = input(prompt,s)

The string prompt will be displayed to the user. The s is an optional argument, used only if

you want the input to be read in as a string. Heres an example m-file, script1.m that makes

use of the function we created earlier:

% Script1 increment a matrix of ones by some user-specified value, v

B = ones(3,3);

v = input(What value do you want to increment by? );B = incrementor(B,v)


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When we run script1.m, this is what we get:

>> script1

What value do you want to increment by? 2

B =

3 3 3

3 3 3

3 3 3

File I/O

MATLAB allows you to save matrices and read them in later. The simplest way to do this is

using the commands save and load. Typing in save A saves matrix A to a file called

A.mat. If you want to read in matrix A later, just type load A. You can also use the load

command to read in ASCII files, as long as they are formatted correctly. Formatted correctly

means that the number of columns in each line is the same and the columns are delimited with

a space. Suppose you have a file called datafile.dat that contains the following lines:

12.5 6 9

1 3.5 125

2 4 0

Notice that the columns do not have to be lined up exactly, as long as there are the same

numbers of them on each line. You can read this into MATLAB by typing load datafile.dat.

MATLAB will read the file contents into a matrix called datafile (without the file extension).

Making plots

Now that you can load data into MATLAB and easily manipulate it, youll want to be able to

display the results in a meaningful (and hopefully aesthetically pleasing) way. Lets create

some sample data for an example of a simple linear plot:

>> x = 1:10;

>> y1 = x.^2;

>> y2 = 2.*y1;

You can plot it using the plot command:

>> plot(x,y1)

Suppose you want to plot only the data points, without the line between them:

>> plot(x,y1,ko)

This will plot the data with black os (k for the color black, and o to plot os) instead of the

default blue line. To see all the options for plotting colors/characters, type help plot.


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Suppose you want to make a second plot, of y2. If you type plot(x,y2) it will overwrite the

plot that we already have. If you want to be able to look at both plots at once, you can plot y2

in a new window. Type figure to open a new figure window:

>> figure

>> plot(x,y2)

However, you may want to plot y1 and y2 on the same set of axes. Use the hold command to

hold the current plot and axes properties. First, return to figure 1:

>> figure(1)

>> hold on

>> plot(x,y2)

You can put multiple individual plots in the same figure window using the subplot command.

Type help subplot for more information. Once youre done with your plot, youll probably

want to label the axes:

>> xlabel(x)

>> ylabel(y)

You can also give it a title:

>> title(My plot)

you can change colours using the colormap command. MATLAB has several built-in

colormaps, or you can make your own. For example, to change to a black-and-white color

scheme, type:

>> colormap(gray)

A brief list of plotting commands for 2-D data is below:

2-D

plot linear plot

loglog log-log plot

semilogx semi-log plot

semilogy semi-log plot

Once youre all done with your plots, you can save them to look at lateruse saveas to save

as a figure file. You can also make images of your figures to use in posters, publications, etc.

Use the print command to export figures in any image format (e.g., ps, eps, tif, jpg).

Advanced operations

Theres a lot more that you can do with MATLAB than is listed in this handout. Check out the

MATLAB help or one of the Other Resources if you want to learn more about the followingmore advanced tools:


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Numerical integration (quad)

Discrete Fourier transform (fft, ifft)

Statistics (mean, median, std, var)

Curve fitting (cftool)

Signal processing (sptool)

Numerical integration of systems of ODEs (ode45)

Getting help

MATLAB has an interactive Help Desk which includes documentation and examples for

pretty much everything youd want to do. However, it can be slow to navigate, so if you just

want to find out how to use a particular function, its easier to use the help command. Useful

commands for accessing MATLAB help are:

Help desk starts the MATLAB interactive help browser

help name displays documentation for function/command name.

look for string searches all help files for string in the description (first comment line), and

displays the function names with the description.

Suppose you want to find out how to use the tangent function, tan(x).

>> help tan

TAN Tangent of argument in radians.

TAN(X) is the tangent of the elements of X.

See also atan, tand, atan2.

Overloaded functions or methods (ones with the same name in other directories) help

sym/tan.m

Reference page in Help browser

doc tan

Suppose you want to find out how to use the tangent function, but you dont know what it is

called.

>> lookfor tangent

ACOT Inverse cotangent, result in radian.

ACOTD Inverse cotangent, result in degrees.

ACOTH Inverse hyperbolic cotangent.

ATAN Inverse tangent, result in radians.

ATAN2 Four quadrant inverse tangent.

ATAND Inverse tangent, result in degrees.ATANH Inverse hyperbolic tangent.


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COT Cotangent of argument in radians.

COTD Cotangent of argument in degrees.

COTH Hyperbolic cotangent.

TAN Tangent of argument in radians.

TAND Tangent of argument in degrees.

TANH Hyperbolic tangent.

4. THE DIGITAL WATERMARK

Digital watermarking is a technology for embedding various types of information in

digital content. In general, information for protecting copyrights and proving the validity of

data is embedded as a watermark. A digital watermark is a digital signal or pattern inserted into

digital content. The digital content could be a still image, an audio clip, a video clip, a text

document, or some form of digital data that the creator or owner would like to protect. The

main purpose of the watermark is to identify who the owner of the digital data is, but it can also


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identify the intended recipient. Why do we need to embed such information in digital content

using digital watermark technology?

The Internet boom is one of the reasons. It has become easy to connect to the Internet

from home computers and obtain or provide various information using the World Wide Web

(www). All the information handled on the Internet is provided as digital content. Such digital

content can be easily copied in a way that makes the new file in distinguishable from the

original. Then the content can be reproduced in large quantities. For example, if paper bank

notes or stock certificates could be easily copied and used, trust in their authenticity would

greatly be reduced, resulting in a big loss. To prevent this, currencies and stock certificates

contain watermarks. These watermarks are one of the methods for preventing counterfeit and

illegal use. Digital watermarks apply a similar method to digital content. Watermarked content

can prove its origin, thereby protecting copyright. A watermark also discourages piracy by

silently and psychologically deterring criminals from making illegal copies.

4.1 Principle of digital watermarks

A watermark on a bank note has a different transparency than the rest of the note when

a light is shined on it. However, this method is useless in the digital world. Currently there are

various techniques for embedding digital watermarks. Basically, they all digitally write desired

information directly onto images or audio data in such a manner that the images or audio data

are not damaged. Embedding a watermark should not result in a significant increase or

reduction in the original data. Digital watermarks are added to images or audio data in such a

way that they are invisible or inaudible unidentifiable by human eye or ear. Furthermore,

they can be embedded in content with a variety of file formats. Digital watermarking is the

content protection method for the multimedia era. Materials suitable for watermarking Digital

watermarking is applicable to any type of digital content, including still images, animation, and

audio data. It is easy to embed watermarks in material that has a comparatively high

redundancy level ("wasted"), such as colour still images, animation, and audio data; however, it

is difficult to embed watermarks in material with a low redundancy level, such as black-and-

white still images To solve this problem, we developed a technique for embedding digital

watermarks in black-and-white still images and a software application that can effectively

embed and detect digital watermarks.


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4.2 Structure of a digital watermark

The structure of a digital watermark is shown in the following figures

Fig 4.1 Structure of digital watermarking

The material that contains a digital watermark is called a carrier. A digital watermark is

not provided as a separate file or a link. It is information that is directly embedded in the carrier

file. Therefore, simply viewing the carrier image containing it cannot identify the digitalwatermark. Special software is needed to embed and detect such digital watermarks. Kowas

Stegano Sign is one of these software packages. Both images and audio data can carry

watermarks. A digital watermark can be detected as shown in the following illustration

5. THE IMPORTANCE OF DIGITAL WATERMARKS

The Internet has provided worldwide publishing opportunities to creators of various

works, including writers, photographers, musicians and artists. However, these same

opportunities provide ease of access to these works, which has resulted in pirating. It is easy to

duplicate audio and visual files, and is therefore probable that duplication on the Internet occurs

without the rightful owners' permission. An example of an area where copyright protection

needs to be enforced is in the on-line music industry. The Recording Industry Association of

America (RIAA) says that the value of illegal copies of music that are distributed over the


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Internet could reach $2 billion a year. Digital watermarking is being recognized as a way for

improving this situation. RIAA reports that "record labels see watermarking as a crucial piece

of the copy protection system, whether their music is released over the Internet or on DVD-

Audio". They are of the opinion that any encryption system can be broken, sooner or later, and

that digital watermarking is needed to indicate who the culprit is. Another scenario in which the

enforcement of copyright is needed is in newsgathering. When digital cameras are used to

snapshoot an event, the images must be watermarked as they are captured. This is so that later,

image's origin and content can be verified. This suggests that there are many applications that

could require image

Fig 5.1Internet imaging of watermarking

Watermarking, including Internet imaging, digital libraries, digital cameras, medical

imaging, image and video databases, surveillance imaging, video-on-demand systems, and

satellite-delivered video.

6. THE PURPOSES OF DIGITAL WATERMARKS

Watermarks are a way of dealing with the problems mentioned above by providing a

number of services: They aim to mark digital data permanently and unalterably, so that the

source as well as the intended recipient of the digital work is known. Copyright owners can

incorporate identifying information into their work. That is, watermarks are used in the

protection of ownership. The presence of a watermark in a work suspected of having been

copied can prove that it has been copied. By indicating the owner of the work, they

demonstrate the quality and assure the authenticity of the work. With a tracking service, owners


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are able to find illegal copies of their work on the Internet. In addition, because each purchaser

of the data has a unique watermark embedded in his/her copy, any unauthorized copies that

s/he has distributed can be traced back to him/her. Watermarks can be used to identify any

changes that have been made to the watermarked data. Some more recent techniques are able to

correct the alteration as well.

6.1 Overview of Copyright Law

"In essence, copyright is the right of an author to control the reproduction of his

intellectual creation". When a person reproduces a work that has been copy righted, without the

permission of the owner, s/he may be held liable for copyright infringement. To prove

copyright infringement, a copyright owner needs to prove 2 things. S/he owns the copyright in

the work, and The other party copied the work (usually determined by establishing that the

other party had access to the copyrighted work, and that the copy is "substantially similar" to

the original).In cases where it cannot be said that the owner's work and the possible illegal copy

are identical, the existence of a digital watermark could prove guilt. The damages charge can be

higher if it can be proven that the party's conduct constitutes will full infringement; that is, s/he

copied the work even though s/he knew that it was copyrighted (for example, copying even

after having discovered a watermark in the work).

7. LOCATION OF WATERMARKS

7.1 Random Marks

The most economical way to produce your watermark is to have it appear in a random

fashion on the finished sheet. in this display, one complete watermark, or i some instances part

of a watermark, will appear on each 8Z/x x 11 sheet. Depending on the size of the design,

marks can be furnished to appear on a higher frequency staggered or uniformly. However, the

location of any random mark will vary from sheet to sheet and cannot be controlled to appear in

the same exact position on each and every sheet. A random mark will appear in the same line

vertically on the sheet, buy may be in different locations from top to bottom


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Fig 7.1Random Marks

7.2 Localized Watermarks

If more critical positioning of your watermark is required, you might want to consider a

localized watermark. Electronically controlled positioning guarantees that the mark will appear

within (plus or minus) one-half (1/2) inch of the position specified (in any direction) when the

sheet is cut to letterhead size. However, approximately 80% of the total quantity ordered will

usually appear within (plus or minus) one-quarter (1/4) inch of the position specified. Paper in

rolls cannot be localized but design can be centered from side to side parallel to grain direction.For many business firms, localized watermarks are most generally centered in the lower two-

thirds of the sheet so that it will appear centered in the body of the letterhead or corresponding

copy. It is also often localized in the lower right or lower left hand corner of the sheet, where

typing seldom occurs.

Fig 7.2 Localized Watermarks

7.3 Paraded Marks


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The Dandy roll for this type of watermarking is usually designed to guarantee two full

marks and a portion of a third mark appearing in each 8Z/x * 11 sheet. These marks can be

paraded across the sheet anywhere ... either vertically or horizontally.

Fig 7.3Paraded Marks

7.4 Staggered Marks

Staggered watermarks are produced in the same manner as paraded marks, but with

some visual variation. They appear in varying locations on each sheet.

Fig 7.4 Staggered Marks

7.5 Watermark Configurations

Perhaps the most confusing part of bond and writing papers is the watermark

configurations; by that we mean how and where the watermarks are impressed on the master

size paper sheet. Once the confusion is cleared up, however, the paper salesperson can guide

printers in ordering the proper watermark configuration for a given job.

7.5.1 Head-to-foot

The term head to foot configuration means that on the sheet the head, or top of the

watermark, reads to the bottom, or foot, of the watermark above. Therefore, on the master sheet

all watermarks read correctly from one side of the sheet. As you can see in the diagram, the


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watermark dies run across the Dandy roll, imprinting the watermark perpendicular to the paper

grain. The result: master sheets watermarked in the head-to-foot configuration will be

watermarked across the grain of the paper. Because in the paper manufacturing process the web

stretches in the grain direction, the watermark can travel from the bottom edge to the top edge

in succeeding letterheads. Also, the watermark may be cut with part of it appearing at the

bottom of the letterhead and part of it appearing at the top. This pattern usually results in a

grain short parent sheet size such as 29 x 21; 34 x 24; 38 x 24; 34 x 22; 35 x 22Z\x. Final

Letterheads cut from the above will be grain long. The printer will print one row of

mastheads along one edge and another row across the centre of the press sheet.

Fig 7.5 Head-to-foot

7.5.2 Head-To-Head

In this configuration, the head of one watermark readds to the head of the watermarkabove, which is upside down, on the master sheet. Therefore, on the master sheet half of the

watermarks are readable while the other half appear upside down. The watermark dies run

around the Dandy roll, imprinting along the paper grain, as you can see in the diagram. The

result: master sheets watermarked head-to-head configuration will be watermarked along the

grain direction of the paper. Because the paper web stretches in the grain direction, the

watermark can drift from the right-hand side of the letterhead to the left-hand side in

succeeding letterheads. Thus, in some letterheads part of the watermark may appear on one side


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of the letterhead and part on the other side. Although it may be cut, there is always a complete

mark on each 8Z\x * 11.

This pattern usually results in a grain long parent sheet size such as: 21 x 29; 24 x 38;

22 x 34; 22Z/x * 35. Final letterheads cut from the above will be grain short. All mastheads

will print across the center of the sheet providing better register control. These 3 grain long

parent sheets yield a grain long final letterhead. All-Over this watermark position is used

almost exclusively for the manufacturer of paper for envelope conversion where watermark

placement is not as important. The all-over pattern features a head-to-foot staggered watermark,

and can be either cross grain or long grain. The all-over watermark is often attractive to

individuals or companies who choose to design a nonstandard size letterhead. For example, a

6x9 size letterhead folded in half lengthwise to fit a envelope would result in some of the

watermark showing in each letterhead, with no concern for laying out the press sheet.

Fig 7.6 Head-To-Head

8. DIGITAL WATERMARK TYPES AND TERMS

Watermarks can be visible or invisible

Visible watermarks are designed to be easily perceived by a viewer (or listener). They

clearly identify the owner of the digital data, but should not detract from the content of the data.

Invisible watermarks are designed to be imperceptible under normal viewing

(or listening) conditions; more of the current research focuses on this type of watermark than

the visible type.

Both of these types of watermarks are useful in deterring theft, but they achieve this in

different ways. Visible watermarks give an immediate indication of who the owner of the


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digital work is, and data watermarked with visible watermarks are not of as much usefulness to

a potential pirate (because the watermark is visible). Invisible watermarks, on the other hand,

increase the likelihood of prosecution after the theft has occurred. These watermarks should

therefore not be detectable to thieves, otherwise they would try to remove it; however, they

should be easily detectable by the owners. A further classification of watermarks is into

Fragile, semi-fragile or robust

Table 8.1 Comparing invisible and visible watermarking schemes

One of the major disadvantages of visible watermarking lies in the visibility of markedpatterns. Though embedded patterns are claimed to be unobtrusive, content viewers still feel

annoying about the degrading visual quality. Consequently, applications of visible

watermarking are often limited to content browsing or previewing. As for the invisible

watermarking, though good fidelity is always guaranteed, the requirement that an explicit

extraction module must exist in the extraction side does introduce additional deployment cost

and security problems. To make things worse, in scenarios such as conveying metadata (e.g.

annotations, contextual information or copyright claims) to users of legacy display deviceslacking modern updating/renewing capability, deploying extractor of invisible watermarking

schemes is totally infeasible.

Fragile

Watermark is embedded in digital data to for the purpose of detecting any changes that

have been made to the content of the data. They achieve this because they are distorted, or

"broken", easily. Fragile watermarks are applicable in image authentication systems.

Semi-fragile


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Watermarks detect any changes above a user-specified threshold. Robust watermarks

are designed to survive "moderate to severe signal processing attacks". Watermarks for images

can further be classified into spatial or spectrum watermarks, depending on how they are

constructed:

Spatial

Watermarks are created in the spatial domain of the image, and are embedded directly

into the pixels of the image. These usually produce images of high quality, but are not robust to

the common image alterations.

Spectral

(Or transform-based) watermarks are incorporated into the image's transform

coefficients. The inverse-transformed coefficients form the watermarked data.

Perceptual

Watermarks are invisible watermarks constructed from techniques that use models of

the human visual system to adapt the strength of the watermark to the image content. The most

effective of these watermarks are known as image-adaptive watermarks. Finally,

blind watermarking techniques are techniques that are able to detect the watermark in a

watermarked digital item without use of the original digital item.

9. GENERIC WATERMARKING SYSTEM

Digital watermarking algorithms are composed of three parts, namely, watermark

embedding algorithm, watermark extraction algorithm and watermark detection algorithm. A

general watermark system phases is shown in Figure 2.1.


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Figure 9.1 Watermark Lifecycle Phase

During embedding process, an algorithm accepts the host and the data to be embedded

and produces a watermarked signal. The watermarked signal is then transmitted or stored. If a

person makes a modification, then the digital content is said to be attacked. A watermark attack

is an attack on digital data where the presence of a specially crafted piece of data can be

detected by an attacker without knowing the encryption key. Special attention has to be paid to

the kind of attacks as they can help to develop better watermarking techniques and defined

better benchmarks. According to, watermark attacks can be classified into four main groups:

(i) Simple attacks: These types of attacks attempt to damage the embedded watermark by

modifications of the whole frame without any effort to identify and isolate the watermark.

Examples include frequency based compression, addition of noise, cropping and correction.

(ii) Detection-disabling attacks: These attempts to break correlation and to make detection of

the watermark impossible. Geometric distortion like zooming, shift in spatial or (in case of

video) temporal direction, rotation, cropping or pixel permutation, removal or insertion are

used.

(iii) Ambiguity attacks: These attacks the detector by producing fake watermarked data to

discredit the authority of the watermark by embedding several additional watermarks so that it

is not obvious which was the first, authoritative watermark.


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(iv) Removal attacks: The removal attacks estimates the watermark, separate it out and discard

only the watermark. Examples are collusion attack, denoising or exploiting conceptual

cryptographic weakness of the watermark scheme (e.g. knowledge of positions of single

watermark elements).

Detection (often called extraction) is an algorithm which is applied to the attacked

signal to attempt to extract the watermark from it. If the signal was unmodified during

transmission, then the watermark is still present and it can be extracted. In robust watermarking

applications, the extraction algorithm should be able to correctly produce the watermark, even

if the modifications were strong. In fragile watermarking, the extraction algorithm should fail if

any change is made to the signal.

Any watermarking technique has to be evaluated to judge its performance. Three

factors, as given below, must be considered while evaluating an image watermarking

algorithm.

Capacity, i.e. the amount of information that can be put into the watermark and

recovered without errors;

Robustness, i.e. the resistance of the watermark to alterations of the original content

such as compression, filtering or cropping;

Visibility, i.e. how easily the watermark can be discerned by the user.

The desired properties are high capacity, low distortion and high robustness to attacks

or high security. These factors are interdependent; for example, increasing the capacity will

decrease the robustness and/or increase the visibility. Therefore, it is essential to consider

all three factors for a fair evaluation or comparison of watermarking algorithms

10.CLASSIFICATION OF WATERMARKING SCHEMES

Digital watermarking schemes can be broadly classified into four categories, namely,

Robust, Fragile, Semi-fragile and Reversible. While, as mentioned previously, imperceptibility,

low embedding distortion and security are the common requirements of all classes, each


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different category of scheme has different characteristics and, thus, is suitable for different

applications. For example, while robustness is an essential requirement for copyright

applications, it has no role in most authentication applications. This section provides a brief

explanation of each of these schemes along with application areas where they can be applied.

10.1. Robust Watermarking Schemes

Robust watermarking algorithm aims at mixing a no perceptible communication channel

with image data, in such a way that the capacity of this extra channel degrades smoothly with

the distortion the watermarked content undergoes. This class of schemes has found its

applications in many areas, which includes the following.

Ownership proof and identification

Transaction tracking/fingerprinting

Copy control/copy prevention

Broadcast monitoring

There are two major approaches to the designing of robust watermarking schemes namely

spread spectrum (SS) watermarking and quantization index modulation (QIM) watermarking.

The idea behind SS-based schemes is to treat the watermark as a narrow-band signal and

embed each bit in multiple samples of the host media, which is treated as a wide-band signal.

The common approach taken by QIM-based schemes is, first, to establish an association

between a set of watermarks and another set of quantizes with their codebooks predefined

according to the watermarks. Then to embed a watermark, a set of features are extracted from

the host media and quantized to the nearest code of the quantize corresponding to the

watermark. For both types of schemes, a common practice for ensuring low distortion and

reducing the interference between the watermark and the host media is the so called informed

embedding in which the information about the host media is exploited by the embedded.

10.2. Fragile Watermarking Schemes

In contrary to robust watermarking, fragile watermarks are sensitive to all kind of

malicious and non-malicious manipulations, i.e. when manipulated the watermarks are

expected to be completely destroyed. Therefore, they are useful for the following applications.


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Authentication

Content-integrity verification

An effective fragile watermarking scheme must have the capability of thwarting theattacks, such as cut-and-paste (i.e. cutting one region of the media and pasting it somewhere

else in the same or another media) and vector quantization (i.e. forging a new marked image by

combining some regions of taken from different authenticated media while preserving their

relative positions. Some recent fragile schemes can be found in. However, fragile watermarks

are sensitive not only to malicious manipulations but also to content-preserving operations such

as lossy compression, transcoding, bit rate scaling, and frame rate conversion. Unfortunately,

those content preserving operations are sometimes necessary in many Internet and multimedia

applications, making fragile watermarking feasible only in the applications, such as satellite

imagery, military intelligence, and medical image archiving

10.3. Reversible Watermarking Schemes

One limitation of the previously mentioned authentication schemes is that the distortion

inflicted on the host media by the embedding process is permanent. Although the distortion is

often insignificant, it may not be acceptable for some applications. For example, any tiny

distortion of an image, even if it were a result of the watermark embedding process itself, in the

legal cases of medical malpractice would cause serious debate on the integrity of the image.

Therefore, it is desirable that watermarking schemes are capable of perfectly recovering the

original media after passing the authentication process. Schemes with this capability are often

referred to as reversible watermarking schemes also known as invertible or erasable

watermarking.

The work of search for two unequally represented sets of pixel groups such that

changing the intensity of the elements belonging to one set changes their membership, making

them belong to another set. A binary location map is then created, with each bit corresponds to

one pixel group and the value (either 0 or 1) represents the membership of that pixel group. The

location map subsequently undergoes some form of lossless compression so that its compressed

version can be combined with the watermark, the actual payload, to form a bit stream for

embedding. The embedding is carried out by changing the intensity of the pixel groups in order

to make their membership consistent with the binary value of their corresponding bit in the bit

stream. The extraction is simply a process of checking the membership of each pixel group of


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the watermarked image. If the image passes the authentication process, the original image can

be recovered by uncompressing the location map and then changing the intensity of each pixel

groups so that their intensity become compatible with their actual membership recorded in the

location map.

One of the limitations of all three schemes is that the ratio of the number of members in

the two sets is highly dependent on the host image. Usually images with more details or high-

frequency components tend to have lower ratio, making the location map less compressible,

thus, lowering the embedding capacity of the payload. An interesting scheme with media-

independent embedding capacity is reported in to alleviate this drawback.

11. CONTENT BASED IMAGE WATERMARKING

Many digital watermarking schemes have been proposed in the literature for still images

and videos and are mainly used in applications discussed in the previous chapters. In all these

applications, apart from copyright protection, illegal copy protection, proof of ownership

problems, identification of manipulations, there is a growing need for the authentication of the

digital content. Recently, the searches for more secure watermarking techniques have revealed


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the fact that the content of the images could be used to improve the invisibility and the

robustness of a watermarking scheme. This section the various content based image

watermarking methods

11.1. Human Visual System (HVS)

The notion of using watermark as a masking phenomena with constrains of non-

visibility is performed using the HVS properties. Much research has been done to increase the

robustness and the data hiding capacity of watermarking techniques based on perceptual

properties of the Human Visual System (HVS). Kay and Izquierdo in used a content based

estimation of Just Noticeable Distortion (JND) in frequency domain. To estimate the JND three

image characteristics were considered, namely, texture, edginess and smoothness. Their results

proved that this technique was resilient to most common attacks like geometric image

transformations.

Recently in this work, they considered the texture, luminance, and corner and edge

information of an image to create a mask that makes the watermark addition to the image less

perceptible to the human eyes. The embedding and extraction are done in frequency domain,

thereby gaining robustness again common attacks like compression and filtering. The results

provided are encouraging.

Much research has been done to increase the robustness and the data hiding capacity of

watermarking techniques based on perceptual properties of the Human Visual System (HVS).

The development and improvement of accurate human vision models helps in the design and

growth of perceptual masks that can be used to better hide the watermark information thereby

increasing its security.

Similarly, in the work proposed by, the noise sensitivity of each pixel based on the local

region image content such as texture, edge and luminance information was used to obtain the

JND mask for the image to be watermarked. Then each bit of the watermark is spread spatially

and shaped by pseudo-noise sequence such that its amplitude is kept below the noise sensitive

of the pixel into which it is inserted. Experimental results proved that the technique was

resistant to compression, cropping and noise attacks.

11.2. Independent Component Analysis (ICA)


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DCT and DWT are the two transformation techniques that are widely used in the

watermark embedding process. Recently, researchers have started using ICA for watermarking.

In ICA was applied to the blocks of the host image and that becomes the watermark. The least-

energy independent components of the host were replaced by the high-energy independent

components of the watermark image. The drawback of this scheme is that, for watermark

extraction both the watermark and the host images are required.

This was followed by the work of where the host image, the key image, and the watermark

image as the independent sources. Embedding was done by weighted addition of the key and

the watermark to the host. For watermark extraction, two more mixtures were obtained by

adding the key and the watermark using different weights. ICA was then applied to these

mixtures to separate the host, the key, and the watermark. The host and the key both are

required for watermark extraction

12.FINDING THE SCALING AND EMBEDDING FACTORS

While finding the scaling factors and embedding factors , that the quality of the

watermarked image is not degraded.


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The edge blocks should be least altered to avoid significant distortion of the image. So

one can add only small amount of watermark gray value in the edge block of host

image. This means that scaling factor should be close to, (the maximum value of the

scaling factor) and embedding factor should be close to min, (the minimum valueof the embedding factor).

The distortion visibility is low when the background has strong texture. In a highly

textured block, energy tends to be more evenly distributed among the different AC

DCT coefficients. That means AC DCT coefficients of highly textured blocks have

small variances and we can add more to those blocks. So for convenience, we assume

n to be directly proportional to variance ( ) and n to be inversely proportional to

variance ( ).

Let usdenote the mean gray value of each image block as and that of the image as

. The blocks with mid-intensity values ( =) are more sensitive to noise than that of

low intensity blocks ( < ) as well as high intensity blocks ( > ). This means that

n should increase with as long as ( < ) and should decrease with as long as (> ). For convenience, the relationship between n and is taken to be truncated

Gaussian. The variation of nwith respect to is the reverse of that of . The mean

gray value of each block is given by its DC DCT coefficient.

To confirm to the above requirements we have chosen and n as follows:

The and n for edge blocks are taken to be and minrespectively.

For non-edge blocks and n are computed as:

(1)

(- (2)

Where n, are the normalized values of nand respectively, and is normalized logarithm

of (thevariance of the AC DCT coefficients).


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n and nare then scaled to the ranges ( , ) and ( , )respectively,

where , are the minimum and maximum values of the scaling factor, and

min , max are the minimum and maximum values of the embedding factor. These

are the parameters determining the extent of watermark insertion.

We divide the original image I into 8x8 blocks and find the DCT coefficients of each

block. Let usdenote the DCT coefficients of block n by, cij(n) = 1,2, ... N, where n represents

the position of block in image I (if we traverse the image in a raster-scan manner). N is the total

number of 8x8blocks in the image and given by (row x co1)/64, "row" is the number of rows

and "col" is the number of columns of the image. The normalized mean gray value of block n is

found out using equation (4):

(4)

Where is the maximum value of

The normalized mean gray value of the image I is calculated using equation (5):

) (5)

The variance of the AC DCT coefficients (on) of block n is found using equation (6):

(6)

Where, is the mean of the AC DCT coefficients

The normalized variance of the AC DCT coefficients of block n is of the value given by

equation (7). Let us denote the natural logarithm of as .

(7)

Where, is the maximum value of

13. THE WATERMARKING PROCESS

13.1 Invisible watermarking process


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The invisible watermarking is also carried out in spatial domain. The invisible

watermarking we propose uses logical operation instead of simple addition. This increases the

robustness of the watermark at the same time ensures the quality of the image. Following are

the steps for invisible watermark insertion. Pseudo-random binary-sequence (0,l } of period N

is generated using linear shift register. The period N is equal to the number of pixels of the

image. The watermark is generated by arranging the binary sequence into blocks of size 4x4

or 8x8. The size of the watermark is same as the size of the image. We start with bit-plane k=O

(MSB) of the image I. The watermark is EXO Red with the bit-plane of the image. This

gives the bit-plane for watermarked image. All bit-planes (EXO Red and non-EXO Red) of

the image I are merged to obtain final watermarked image I. If SNR>threshold, then we stop;

otherwise we go to (iv) with k incremented by1 (for next lower bit-plane).

Fig 13.1 Invisible Watermarking

13.2 The Visible Watermarking Process


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In visible watermarking of images, a secondary image (the watermark) is embedded in

a primary (host) image such that watermark is intentionally perceptible to a human observer

whereas in the case of invisible watermarking the embedded data is not perceptible, but may be

extracted/detected by a computer program. Some of the desired characteristics of visible

watermarks are listed below .A visible watermark should be obvious in both colour and

monochrome images. The watermark should be spread in a large or important area of the image

in order to prevent its deletion by clipping. The watermark should be visible yet must not

significantly obscure the image details beneath it. The watermark must be difficult to remove;

removing a watermark should be more costly and labour intensive than purchasing the image

from the owner. The watermark should be applied automatically with little human intervention

and labour

14.INSERTION OF WATERMARK

The steps for watermark insertion are discussed now.

The original image I (to be watermarked) and the watermark image W are divided intoblocks of size 8x8. (Both the images may not be of equal size).


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The DCT coefficients for each block of the original image are found out.

For each block of the original image I, the normalized mean gray value n is computedusing eqn. (4) and are scaled to the range 0.1-1.0.

The normalized image mean gray value p is found out using equation (5).

For the AC DCT coefficients, the normalized variances are computed using equation

(7) and scaled to the range 0.1-1 .o.

The edge blocks are identified using the Sobel edge operator.

The n and n are found by using equations (2)and (3).

The DCT of watermark image blocks are found out.

The nth block DCT coefficient of the host image I is modified using equation (1). TheIDCT of modified coefficients give the watermarked image.

Figure 14.1 Watermark Insertion Process


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Watermark image Visible Watermarking Invisible Watermarking

Figure 14.2

Watermark image Host Image Watermarked Host Image

Figure 14.3

15.MODIFICATIONS TO MAKE THE WATERMARK MORE

ROBUST

The algorithm proposed here and also that of the classification schemes proposed in are

not robust for images having very few objects and large uniform areas like in Fig. (Host

image'). In most of the blocks will be classified to be in one class for this type of image. Thedifferent nand n are sorted and displayed here to get a clear understanding of the situation.

So in either of the cases, it is easy for a digital thief to remove the watermark from the

watermarked image as it would be easy to predict the n and n values. We propose a

modification to our above watermark insertion technique. After getting the values we classify

them into two or three different groups. If more than 1/3 of blocks have the same value then we

generate Gaussian random numbers with mean same as the normalized image mean and

variance 1, and scale to the range [0 (max- min)/2]. Then the numbers are added to


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(subtracted from) n of the largest group. The n values are not disturbed to preserve the

quality of the image. Fig shows the watermarked 'host' image.

16. DIGITAL WATERMARKING APPLICATIONS

Digital watermarking is rapid evolving field, this section identifies digital watermarking

applications and provides an overview of digital watermarking capabilities and useful benefits

to customers. This section deals with some of the scenarios where watermarking is being

already used as well as other potential applications.

VIDEO WATERMARKING

In this case, most considerations made in previous section hold. However, now the

temporal axis can be exploited to increase the redundancy of the watermark. Note that perhaps

the set of attacks that can be performed intentionally is not smaller but definitely more

expensive than for still images.


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AUDIO WATERMARKING

In this case, time and frequency making properties of the human ear are used to conceal

the watermark and make it inaudible. The greatest difficulty lies in synchronizing the

watermark and the watermarked audio file, but techniques that overcome this problem havebeen proposed.

HARDWARE/SOFTWARE WATERMARKING

This is a good paradigm that allows us to understand how almost every kind of data can

be copyright protected. If one is able to find two different ways of expressing the same

information, then one bit of information can be concealed, something that can be easily

generalized to any number of bits. This is why it is generally said that a perfect compression

scheme does not leave room for watermarking. In the hardware context, Boolean equivalences

can be exploited to yield instances that use different types of gates and that can be addressed by

the hidden information bits. Software can be also protected not only by finding

equivalences between instructions, variable names, or memory addresses, but also by altering

the order of non-critical instructions. All this can be accomplished at compiler level.

TEXT WATERMARKING

This problem, which in fact was one of the first that was studied within the information

hiding area, can be solved at two levels. At the Digital Watermarking printout level,

information can be encoded in the way the text lines or words are separated. This facilitates the

survival of the watermark even to photocopying. At the semantic level (necessary when raw

text files are provided), equivalences between words or expressions can be used, although

special care has to be taken not to destruct the possible intention of the author.

EXECUTABLE WATERMARKS

Once the hidden channel has been created it is possible to include even executable

contents, provided that the corresponding applet is running on the end user side.

LABELING

The hidden message could also contain labels that allow for example to annotate images

or audio. For instance, a movie may contain a "watermark" revealing the date of manufacture,


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the actors who were in the film, web sites for selling paraphernalia, as well as the owner of the

movie.

FINGER PRINTING

This is similar to the previous application and allows acquisition devices (such as video

cameras, audio recorders, etc.) to insert information about the specific device (e.g., an ID

number) and date of creation. This can also be done with conventional digital signature

techniques but with watermarking it becomes considerably more difficult to excise or alter the

signature. Some digital cameras already include this feature.

AUTHENTICATION

There are two significant benefits that arise from using watermarking: first, as in the

previous case, the signature becomes embedded in the message, second , it is possible to create

'soft authentication' algorithms that offer a multivalued 'perceptual closeness' measure that

accounts for different unintentional transformations that the data may have suffered (an

example is image compression with different levels),instead of the classical yes/no answer

given by cryptography based authentication. Unfortunately, the major drawback of

watermarking based authentication is the lack of public key algorithms that force either to putsecret keys in risk or to resort to trusted parties. Certification is an important issue for official

documents, such as identity cards or passports. Example on the above of a protected identity

card. The identity number "123456789" is written in clear text on the card and hidden as a

digital watermark in the identity photo. Therefore switching or manipulating the identity photo

will be detected Digital watermarking allows to mutually link information on the documents.

That means that some information is written twice on the document: for instance, the name of a

passport owner is normally printed in clear text and is also hidden as an invisible watermark inthe photo of the owner. If anyone would intend to counterfeit the passport by replacing the

photo, it would be possible to detect the change by scanning the passport and verifying the

name hidden in the photo does not match any more the name printed on the passport.

COPY AND PLAYBACK CONTROL

The message carried by the watermark may also contain information regarding copy

and display permissions. Then, a secure module can be added in copy or playback equipment toautomatically extract this permission information and block further processing if required. In


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order to be effective, this protection approach requires agreements between content providers

and consumer electronics manufacturers to introduce compliant watermark detectors in their

video players and recorders. This approach is being taken in Digital Video Disc (DVD).

SIGNALING

The imperceptibility constraint is helpful when transmitting signalling information in

the hidden channel. The advantage of using this channel is that no bandwidth increase is

required. An interesting application in broadcasting consists in water marking commercials

with signalling information that permits an automatic counting device to assess the number of

times that the commercial has =been broadcast during a certain period. An alternative to this

would require complex recognition software.

FORENSIC TRACKING

Forensic tracking locates the source of the content. The key advantage of digital

watermarking is that it enables tracking of the content to where it leaves an authorized path.

E-COMMERCE/LINKING

The digital watermarking enables the user to purchase or access information about the

content, related content, or items with in the content.

COUNTERFEIT DETERRENCE

Using digital watermarks is being employed by national governments and central banks

to protect the integrity of currencies across the world.

BROADCAST MONITORING

Tracks and monitors where, when and how content is being aired via cable, satellite

and terrestrial delivery

Automates manual reporting system, resulting in cost effective tracking and reporting

solution

Real-time reporting enables faster responsiveness to broadcast information

(e.g. programming changes, ad frequency changes, etc.)


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`

17. RESULT

Host Image: Watermark Image:

WATER MARKED IMAGE:


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18. CONCLUSION

A visible watermarking technique has been proposed in the DCT domain. A mathematical

model has been developed for this purpose exploiting the texture sensitivity of the HVS. We

have also proposed a modification to increase the robustness of the watermark when used for

images with very few objects. For more robustness, the watermark should not be made publicly

available; the watermark should be used in different sizes and should be put in different

portions for different images. We have used lower values of and min and max, and higher

values of minand max to make the watermark more prominent even when the images are

printed on paper. But when the watermarked images are to be viewed only through the internet,

the typical values of min, max, min and min are 0.95, 0.98, 0.07 and 0.17 respectively.

The visible watermark can be used in digital TV, digital library, ecommerce etc. We are now


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trying to incorporate a mathematical model that takes more characteristics of the human visual

system into consideration.

Relevant lemmas and theorems are described and proved to demonstrate the

reversibility of the compound mappings for lossless reversible visible watermarking. The

compound mappings allow different types of visible watermarks to be embedded, and two

applications have been described for embedding opaque monochrome watermarks as well as

translucent full-colour ones. A translucent watermark is clearly visible and visually appealing,

thus more appropriate than traditional transparent binary watermarks in terms of advertising

effect and copyright declaration. The two-fold monotonically increasing property of compound

mappings was defined and an implementation proposed that can provably allow mapped values

to always be close to the desired watermark if colour estimates are accurate. Also described are

parameter randomization and mapping randomization techniques, which can prevent illicit

recoveries of original images without correct input keys. Experimental results have

demonstrated the feasibility of the proposed method and the effectiveness of the proposed

security protection measures. Future research may be guided to more applications of the

proposed method and extensions of the method to other data types other than bitmap images,

like DCT coefficients in JPEG images and MPEG videos.


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19. DIGITAL WATERMARKING - FUTURE TRENDS

Business of online delivery and distribution via CD/removabledisks of multimedia products face huge obstacles due to unlimited perfect copying andmanipulation at the user end.

Digital watermarking is the technology used for copy control, media identification, tracing and

protecting content owner's rights. The internet is an open network, being increasingly

used for delivery of digital multimedia contents. In the digital format, content is

expressed as streams of ones and zeroes that can be transported flawlessly. The

contents can be copied perfectly inf init e times. A user can also manipulate these files.

However, good business senses necessitates two transaction mechanisms - content protectionand secure transport over the internal. This unique distribution may be hash value or textual

description. Registration authority allots a unique identification number to the

content and archives these two for future reference. Th is ma rk i s se cr et ly an d

securel y merged with original content. Watermarked content's quali ty is

minimally degraded. Owner can also attach a 'label' that is related to a unique identification

number. Cryptology is an effective solution for secure transport of copyright protected. .

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