Secure Hybrid DWT DCT Watermarking

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 & Principal2
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

193
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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Secure Hybrid DWT DCT Watermarking

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