50120140504020 2

International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),

ISSN 0976 - 6375(Online), Volume 5, Issue 4, April (2014), pp. 186-193 © IAEME

186

SECURE HYBRID WATERMARKING USING DISCRETE WAVELET

TRANSFORM (DWT) & DISCRETE COSINE TRANSFORM (DCT)

Neetu Rathi 1

and Dr. Anil Kumar Sharma2

M. Tech. Scholar1, Professor & Principal

2

Department of Electronics & Communication Engineering,

Institute of Engineering & Technology, Alwar-301030 (Raj.), India

ABSTRACT

Digital image watermarking is a technique used for copyright protections of digital data.

A digital watermark is a kind of marker covertly embedded in a noise-tolerant signal such as audio or

image data. It is typically used to identify ownership of the copyright of such signal. This paper

presents an efficient hybrid digital watermarking technique using DWT & DCT for copy right

protection. In addition, a concise introduction about digital marking is presented along with its

properties, techniques & attacks. The simulation results show that this algorithm has good robustness

for some common image processing operations & also gives improved results in terms of PSNR &

Correlation coefficients.

Keyword: Attacks, Authentication, DCT, DWT, PSNR.

1. INTRODUCTION

Everyday tons of data is embedded on digital media or distributed over the internet. The data

so distributed can easily be imitated without error, putting the rights of their owners at risk. Even

when encrypted for distribution, data can easily be decrypted and copied. One way to discourage

illegal duplication is to insert information known as watermark, into potentially vulnerable data in

such a way that it is impossible to separate the watermark from the data. These challenges motivated

researchers to carry out intense research in the field of watermarking. A watermark is a form, image

or text that is impressed onto paper, which provides indication of its authenticity. Digital

watermarking is an extension of the same concept. Digital watermarking is the process of embedding

information into digital multimedia content such that the information can be extracted or detected at

the later stage for a variety of purposes including copy prevention and control [1]. A digital

INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &

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ISSN 0976 – 6367(Print)

ISSN 0976 – 6375(Online)

Volume 5, Issue 4, April (2014), pp. 186-193

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International Journal of Computer Engineering and Technology (IJCET), ISSN 0976

ISSN 0976 - 6375(Online), Volume 5, Issue 4, April (2014), pp.

watermark is used for this purpose which is a digital signal inserted into a digital image and may also

serve as a digital signature [2]. Digital watermarking is also to be contrasted with public

encryption, which also transforms original files into another form. Unlike encryption, digital

watermarking leaves the original image uncontaminated and recognizable. In addition, digital

watermarks, as signatures, may not be validated without special software. Further, decrypted

documents are far from of any residual effects of encryption, whereas digital watermarks are

designed to be persistent in viewing, printing, or subsequent retransmission or dissemination.

are two types of watermarks: visible watermark and invisible waterma

concentrated on implementing watermark in image. The main factor of consideration for any

watermarking scheme is its robustness to various attacks. Watermarking dependency on the original

image increases its robustness but at the

imperceptible.

2. CLASSIFICATION OF WATERMARKING

The classification of watermarks and watermarking techniques is very broad. These are

divided into various categories [5, 6, 7] based on

the type of Document it can be divided into four categories

Watermarking, Audio Watermarking

Fig. 1: Classification of watermarking Techniques

On the basis of domain used for watermarking the techniques fall in two categories: those

which use spatial domain and those which use transform domain. Spatial

technologies change the intensity of original image or gray levels of its p

watermarking is simple and with low computing complexity, because no frequency transform is

needed. However, there must be trade

common image processing and noise. Trans

the transformed image. According to the human perception [5, 6, 9],

watermark, Invisible-Robust watermark

According to the application it is either source based or destination based. Source

are desirable for ownership identification or authentication where a unique watermark identifying the

owner is introduced to all the copies of a particular image being distri

watermark could be used for authentication and to determine whether a received image or other

electronic data has been tampered with. The watermark could also be destination based where each

distributed copy gets a unique watermark id

watermark could be used to trace the buyer in the case of illegal reselling.

enable watermarking in the spatial domain. The simplest is just to flip the lowest

International Journal of Computer Engineering and Technology (IJCET), ISSN 0976

6375(Online), Volume 5, Issue 4, April (2014), pp. 186-193 © IAEME

187


serve as a digital signature [2]. Digital watermarking is also to be contrasted with public

ms original files into another form. Unlike encryption, digital



nts are far from of any residual effects of encryption, whereas digital watermarks are

designed to be persistent in viewing, printing, or subsequent retransmission or dissemination.

are two types of watermarks: visible watermark and invisible watermark. In this paper we have



image increases its robustness but at the same time we need to make sure that the watermark is

CLASSIFICATION OF WATERMARKING


divided into various categories [5, 6, 7] based on different criterions as shown in Fig

can be divided into four categories i.e. Text Watermarking

Audio Watermarking and Video Watermarking.

Fig. 1: Classification of watermarking Techniques


which use spatial domain and those which use transform domain. Spatial-domain watermarking

technologies change the intensity of original image or gray levels of its pixels. This kind of


needed. However, there must be trade-offs between invisibility and robustness, and it is hard to resist

common image processing and noise. Transform-domain watermarking embeds the watermark into

According to the human perception [5, 6, 9], it can be divided into Visible

Robust watermark, Invisible-Fragile watermark and Dual watermark

either source based or destination based. Source-


owner is introduced to all the copies of a particular image being distributed. A source



distributed copy gets a unique watermark identifying the particular buyer. The destination

watermark could be used to trace the buyer in the case of illegal reselling. Several different methods

enable watermarking in the spatial domain. The simplest is just to flip the lowest-order bit of ch



serve as a digital signature [2]. Digital watermarking is also to be contrasted with public-key

ms original files into another form. Unlike encryption, digital



nts are far from of any residual effects of encryption, whereas digital watermarks are

designed to be persistent in viewing, printing, or subsequent retransmission or dissemination. There

rk. In this paper we have



same time we need to make sure that the watermark is


ig.1. According to

Text Watermarking, Image


domain watermarking

ixels. This kind of


offs between invisibility and robustness, and it is hard to resist

domain watermarking embeds the watermark into

can be divided into Visible

Dual watermark.

-based watermark


buted. A source-based



entifying the particular buyer. The destination -based

Several different methods

order bit of chosen



188

pixels. This works well only if the image is not subject to any change. A more robust watermark can

be embedded by superimposing a symbol on picture. The resulting mark may be visible or invisible,

depending upon the intensity value. Picture cropping, e.g., (a common operation of image editors),

can be used to remove the watermark.

Spatial watermarking can also be applied using color separation. In this way, the watermark

appears in only one of the color bands. This renders the watermark visibly subtle such that it is

difficult to identify under regular viewing. However, the mark appears immediately when the colors

are separated for printing. This renders the document useless for the printer unless the watermark can

be removed from the color band. This approach is used commercially for journalists to inspect digital

pictures from a photo-stockhouse before buying unmarked versions. Watermarking can be applied in

the frequency domain (and other transform domains) by first applying a transform like the Fast

Fourier Transform (FFT). In a similar manner to spatial domain watermarking, the values of chosen

frequencies can be altered from the original. Since high frequencies will be lost by compression or

scaling, the watermark signal is applied to lower frequencies, or better yet, applied adaptively to

frequencies that contain important information of the original picture. Since watermarks applied to

the frequency domain will be dispersed over the whole of the spatial image upon inverse

transformation, this method is not as vulnerable to defeat by cropping as the spatial technique.

However, there is more a trade-off here between invisibility and decodability, since the watermark is

in effect applied indiscriminately across the spatial image.

3. ATTACKS ON WATERMARKS

A watermarked image is likely to be subjected to certain manipulations [2, 13], some

intentional such as compression and transmission noise and some intentional such as cropping,

filtering, etc. The main type of attacks is as follows.

• Active Attacks: Here, the hacker tries intentionally to remove the watermark or simply make

it unnoticeable. This is a big issue in copyright protection, fingerprinting or copy control for

example.

• Passive attacks: In this case, the attacker is not trying to remove the watermark but simply

trying to determine if a given mark is existing or not. As the reader should understand,

protection against passive attacks is of the greatest importance in covert communications

where the simple knowledge of the presence of watermark is often more than one want to

grant.

• Collusion attacks: In collusive attacks [2], the goal of the hacker is the same as for the

active attacks but the process is somewhat different. In order to remove the watermark, the

hacker uses several copies of the same data, containing each different watermark, to

construct a new copy without any watermark. This is a problem in fingerprinting

applications (e.g. in the film industry) but is not the widely spread because the attacker must

have access to multiple copies of the same data and that the number needed can be pretty

important.

• Forgery attacks: This is probably the main concern in data authentication. In forgery

attacks, the hacker aims at embedding a new, valid watermark rather than removing one. By

doing so, it allows him to make change in the protected data as he wants and then, re-inserts

a new given key to replace the destructed (fragile) one, thus making the corrupted image

seems genuine.



189

4. PROPOSED ALGORITHM AND SIMULATION

In this work an algorithm is proposed for secure hybrid digital watermarking using DWT &

DCT. For this a word “Hi” is used as a watermark & the image “lena” is used as a cover image. This

watermark is first decomposed into equal parts in the form of binary matrix (0,1). Then the size of

watermark image or message image is checked in comparison to the cover image. The size of the

watermark should not be greater than that of cover image so that it can hide behind the cover image.

Next the DWT is applied & the cover image is decomposed into its approximation coefficient’s.

After applying DWT we get low frequency components of the cover image (cA1) & next we set a

key=1982 for security purpose & a value of factor=10 which can vary. Then the watermarked image

is to be hide behind the cover image in an encrypted manner (i.e. changing pixel value of cover

image according to the watermark image). Afterwards extracting of the watermark image is done in a

decrypted manner using DCT so that only a known receiver can decode it. Then PSNR &

Correlation Value are computed for the recovered watermarked image. Fig. 2 shows the steps of

simulation.

(a) Cover image “Lena” (b) Watermark Image “Hi”

(c) Decomposed Watermark (d) Watermarked Image



190

(e) Extracted Watermark (f) Normalized Correlation Plot

Fig. 2: Watermark Embedding & Extraction Using DWT & DCT

Here we have observed that the For Original Image Vs. Extracted Watermark Image,

The value of PSNR = 56.7416, Correlation Value = 1.

Next we are going to simulate the process with Attacks of Gaussian Noise as shown in Fig.3.

(a) Decomposed Image (b) Watermarked Image

(c) Extracted Watermark (d) Normalized correlation plot

Fig. 3: Simulation with Attacks of Gaussian Noise



191

Here we have observed that the For Original Image Vs. Extracted Watermark Image,

The value of PSNR = 56.7109, Correlation Value = 0.9964

Next we go for compression attack as shown in Fig. 4.

(a) Decomposed Watermark (b) Extracted Watermark

(d) Normalized Correlation Plot

Fig. 4: Simulation with Compression Attack

Here we have observed, The value of PSNR = 56.7416, Correlation Value = 1

Next we carry out the Simulation with Salt & Pepper Attack as shown in Fig. 5.



192

(a) Decomposed Watermark (b) Watermarked Image

(c) Extracted Watermark (d) Normalized Correlation Plot

Fig. 5: Simulation with Considering Salt & Peeper Attack

Here we have observed that for Original Image Vs. Salt & Peeper Attacked Watermark

Image, the value of PSNR = 54.1684, Correlation Value = -0.036327

Observation: From Table-1 we can see that with reference to previous work we obtain much better

result in terms of PSNR & Correlation Coefficient. Both parameters are improved for different cases

i. e. without attack & on application of attack.

Table-1: Summary of Results as Compared to Previous Work Various Results Results of

Previous Work

Result 1 using

Hybrid

Technique

without Attack

Result 2 using

Hybrid

Technique with

Attack

Result 3 using

Hybrid

Technique with

Attack

Result 4 using

Hybrid

Technique

with Attack

Techniques� Original EOG

Signal Vs.

Watermarked

Signal

Original Image

Vs. Extracted

Watermark

Image

Original Image

Vs. Gaussian

attacked

Watermark

Image

Original Image

Vs. Compression

attacked

Watermark Image

Original Image

Vs. Salt

&peeper

attacked

Watermark

Image

PSNR 31.552 56.7416 56.7109 56.7416 54.1684

Correlation

Coefficient

0.9965 1 0.9964 1 -0.036327



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5. CONCLUSION

The purpose of this paper is to provide a Hybrid Techniques i.e. combination of DWT & DCT

which provides much security & robustness. The results obtained from the algorithm have provided

simpler and a faster approach to find out the extracted images. The algorithm being proposed here

has been shown to have good efficiency, but it is good enough to extract information from noisy

environment in many application cases as: Biomedical signal processing, Image Processing, Image

de-noising, Satellite Image Resolution, speech processing. Thus using MATLAB Hybrid

Watermarking Techniques are implemented. Then Noise is added to the images in the form of

Attacks. The noise is later removed & the base & watermark images are separated from the

watermarked image. Finally a benchmarking of original & recovered image is done based on PSNR

& correlation values.

REFERENCES

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Technology

digital watermarks

categories watermarking

image data

audio watermarking

digital signal

p watermarking

watermarking scheme

field of watermarking