I43014752

Gurpreet Kaur et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.47-52
www.ijera.com 47 | P a g e
Reusability of Patterns Using Discrete Wavelet Transformation in
Watermarking
Gurpreet Kaur, Kamna Mahajan
M.tech Computer Science, Department of CSE, Rbiebt, Kharar Punjab Technical University, India.
AP,M.tech Computer Science, Department of CSE, Rbiebt, Kharar Punjab Technical University, India
Abstract
Digital image watermarking is hiding information in any form in original image without degrading its perceptual
quality. Watermarking is done for copyright protection of the original data. In this paper, a hybrid and robust
watermarking technique for copyright protection based on Discrete Cosine Transform and Discrete Wavelet
Transform is proposed. Wavelet transform has been applied widely in watermarking research as its excellent
multi-resolution analysis property. The watermark is embedded based on the frequency coefficients of the
discrete wavelet transform. The robustness of the technique is tested by applying noise attacks on the host signal
and here the host signal is the database set containing satellite images.
Keywords-Digital image watermarking; multi-resolution analysis; Discrete Cosine Transform; Discrete
Wavelet Transform; Satellite images database
I. Introduction
Digital information is easy to distribute,
duplicate and modify which leads to the need for
copyright protection techniques. Digital
watermarking technique is one of the solutions to
avoid unauthorized copying or tampering of
multimedia data. Recently many watermarking
schemes have been proposed to address this problem
[1]. Owing to the rapid advancement of the Internet
and multimedia systems in distributed environments,
the transfer of multimedia documents across the
Internet by the digital data owners has become
simple. Thus, there is a raise in concern over
copyright protection of digital contents [7] [8].
Against this background, the data hiding technologies
for digital data like digital watermarking have
attracted enormous attention recently [9].Digital
watermarking utilized in order to High Performance
and Effective Watermarking Scheme for satellite
images 284 avert unauthorized duplication or
exploitation of digital images [10] [11].
The process of digital watermarking
involves the modification of the original multimedia
data to embed a watermark containing key
information such as authentication or copyright
codes. The embedding method must leave the
original data perceptually unchanged. The major
technical challenge is to design a highly robust digital
watermarking technique, which discourages
copyright infringement by making the process of
watermarking removal tedious and costly [2].
Digital watermarking is a covert security
feature for identity documents that enables trusted
authentication of host image like the image of PAN
card and other IDs. Watermarking involves the
transformation of a digital artifact into another token
of the same type [3]. Watermarking is done at the
object-level. Almost all watermarking methods,
which have been proposed today, can provide robust
and secret watermark and against various attacks
such as filtering, data compression, warping,
cropping etc. The watermark is robust and secret due
to the owner keeps the algorithm private [12].
Digital watermarking technology is
emerging as a solution to a broad class of challenges.
There has been great interest in applying watermark
to digital multimedia data for copyright protection,
image authentication and proof of ownership etc.
Image watermarking is finding more and more
support as a possible solution for the protection of
intellectual property rights [13].
There are numerous digital image watermarking
techniques in various domains which are broadly
categorized as:
1. Spatial domain based watermarking techniques
2. Transform domain based watermarking techniques
Spatial domain based watermarking
techniques are rarely preferred over transform
domain based watermarking techniques because the
watermark placed by them can be easily destroyed
and modified by the attackers. Although in transform
domain based techniques there are various other
techniques available like DFT (Discrete Fourier
Transform), DCT (Discrete Cosine Transform) [4].
Watermarking represents an efficient
technology for ensuring data integrity and data-origin
authenticity. Watermarking the process of embedding
data into multimedia element can primarily for
RESEARCH ARTICLE OPEN ACCESS

copyright protection. Because of its growing
popularity, the DWT is commonly used in the
proposed watermarking scheme increase, area
increases so power consumption. In any situation,
satellite images ought to be kept unharmed and they
should be checked for:
 Integrity: this verifies that unauthorized people
have not modified the image.
 Authentication: this verifies whether the image
certainly belongs to the right organization.
In this paper, we have presented an effective
watermarking scheme for checking the integrity and
authenticating satellite images using hybrid transform
[14]. Our proposed scheme makes use of the Discrete
Cosine Transform (DCT) and Discrete Wavelet
Transform (DWT) to form a hybrid transform. The
Daubechies 4 wavelet transform is chosen for DWT
in our watermarking scheme. The watermark
embedding and extraction are performed in a
frequency domain with the help of hybrid transform.
Initially, the DCT is applied into the original image
to block it into 8*8 matrix form and the resultant
matrix is converted into hybrid transformed matrix
with the aid of Daubechies 4 wavelet transform [6].
II. Previous Research
A DWT-SVD based secured image
watermarking for copyright protection using visual
cryptography was proposed by Sushila Kamble,
Vikas Maheshkar, Suneeta Agarwal , Vinay K
Srivastava[1]. They applied the singular value
decomposition along with the Discrete Wavelet
Transform. Since the technique utilizes the properties
of both DWT and SVD the proposed technique was
more robust against different attacks. The robustness
of the technique was justified by giving analysis by
the effect of attacks and still they were able to get
good visual quality of the embedded watermark.
Digital Image Watermarking Based on Super-
Resolution Image Reconstruction was proposed by
Xiangbin Feng, Yonghong Chen, College of
Computer Science & Technology, China [15].They
proposed a novel robustness watermarking based on
SRIR, this method was mainly applied to pre-process
the original image. It also contains the results of tests
performed showing the high robustness of the
algorithm against the attacks of JPEG lossy
compression and salt-and pepper noise, multiplicative
noise, center cutting. In addition, it should be
mentioned that the method with SRIR is extremely
more robust against the attacks of JPEG lossy
compression and salt-and-pepper noise than the
traditional one.
III. Watermarking Process
A watermarking system is as
communication system consisting of three main
elements: an embedder, a communication channel
and a detector. Watermark information is any new
information embedded into the signal itself; at the
receiving end this information is extractable by the
detector. Watermark information is embedded within
the host signal before the watermarked signal is
transmitted over the communication channel, so that
the watermark can be detected at the receiving end
that is at the detector. In the watermarking system we
can say that embedding and extraction are the two
steps in the watermarking [5]. In embedding, some
new information is embedded in to the original image
using some key and at receiving end using the same
key embedded information is extracted which shows
the authentication of the original image [4].
Fig.1 Block diagram of watermarking
3.1 Embedding Technique
The low frequency part contain the detail
information of the image and high frequency part
contain the approximate information of the image so
for no change in the image we choose the high
frequency part or smallest coefficients in the DCT
matrix. The high frequency part is chosen in the DCT
coefficient matrix of the original image which shows
the approximate structure of the image [5].

IV. Hybrid (DCT-DWT)
Various watermarking algorithms that utilize
either the DCT or the DWT exist in frequency
domain. Major benefits of the hybrid approach DWT-
DCT transform algorithm are as following:
 Improved Peak Signal to Noise Ratio (PSNR)
when MSE and RMSE values in satellite images
are greater.
 Produce an effective image watermarking.
 Combined transformations recompense the
disadvantages of each other.
4.1 Discrete Cosine Transform
The Discrete Cosine Transform is a
renowned coding technique employed in image and
video compression algorithms. It is capable of
carrying out de-correlation of the input signal in a
data independent manner [6]. The DCT is a
methodology for the transformation of a signal into
elementary frequency components. The sequences of
n real numbers x1,….., xn are converted into the
sequence of n complex numbers f1,…..fn by the DCT
in accordance with the following formula:
n=1 f1=Σ xk cos [ Π /n j(k+1/2] k=0
4.2 Discrete Wavelet Transform
In general, the multi-resolution wavelet
transform can decompose a signal into low pass and
high pass information. Since the high pass
information usually represents features that contain
sharper variations in time domain. This is a frequency
domain technique in which firstly cover image is
transformed into frequency domain and then its
frequency coefficients are modified in accordance
with the transformed coefficients of the watermark
and watermarked image is obtained which is very
much robust. DWT decomposes image hierarchically,
providing both spatial and frequency description of
the image [4]. It decompose an image in basically
four spatial directions i.e, approximation, horizontal,
vertical and diagonal in result separating the image
into four different components namely LL, LH, HL
and HH. Here first letter refers to applying either low
pass frequency operation or high pass frequency
operations to the rows and the second letter refers to
the filter applied to the columns of the cover image.
 LL level is the lowest resolution level which
consists of the approximation part of the cover
image.
 Rest three levels i.e., LH, HL, HH give the
detailed information of the cover image.
Fig 2- Two – Level DWT
V. Effective Watermarking Scheme
using Hybrid (DCT-DWT)
Input Image
Load watermark image
Blocking of image into 8*8 by applying DCT
Applying inverse DCT
Extraction of rows and columns
Convert the image in vectors
Calculate image watermark which is to be added in
original image
Resultant image is divided in rows and columns
Calculate each block value
Set Threshold
Apply watermark to the block selected after testing
threshold
Inserting watermark to the original loaded image
Resultant watermarked image

VI. Result Analysis
To evaluate and compare the performance of
three techniques i.e., median filter, applying DWT
and DCT-DWT, three parameters are taken into
consideration. These parameters are given by:
Using the value of mean square error,
RMSE is calculated by considering the square-root
value of MSE value and then PSNR (Peak Signal to
Noise Ratio) for the images is calculated which gives
the ratio of required signal to the noise content in the
watermarked image. PSNR is calculated by the
formula:
To carry out the experiments MATLAB R2008a software is used. Results obtained are:
Original Image (image2.bmp) Watermark Image (image1.bmp)
Watermarked Image
Table 1
Comparison between the MSE values using the three techniques
Image name
MSE Value using
Median filter
MSE Value using DWT
Filter
MSE Value using
Watermark algorithm
image1.bmp 32.5818 17.0756 1.4641
image2.bmp 19.3256 15.8987 0.8393
image3.bmp 189.5386 20.2523 1.6718
image4.bmp 20.4806 18.9561 1.5313
image5.bmp 18.0187 17.0401 1.6957
0
20
40
60
80
100
120
140
160
180
200
MSE Variations
MSEValue using Median
filter
MSEValue using DWT Filter
MSEValue using Watermark
algorithm

Table 2
Comparison between the RMSE values using the three techniques
Image name
RMSE Value using
Median filter
RMSE Value using
DWT Filter
RMSE Value using
Watermark algorithm
image1.bmp 5.708 4.1323 1.21
image2.bmp 4.3961 3.9873 0.9161
image3.bmp 13.7673 4.5003 1.293
image4.bmp 4.5256 4.3539 1.2375
image5.bmp 4.2448 4.128 1.3022
Table 3
Comparison between the PSNR values using the three techniques
Image name
PSNR Value using
Median filter
PSNR Value using
DWT Filter
PSNR Value using
Watermark algorithm
image1.bmp 32.977 35.8074 46.3959
image2.bmp 35.2776 36.118 48.9743
image3.bmp 25.3722 35.0625 48.1611
image4.bmp 35.0047 35.3369 44.7914
image5.bmp 35.534 35.8015 45.923
RMSE Variations
0
2
4
6
8
10
12
14
16
im
age1.bm
p
im
age2.bm
p
im
age3.bm
p
im
age4.bm
p
im
age5.bm
p
RMSE Value using Median
filter
RMSE Value using DWT Filter
RMSE Value using Watermark
algorithm
PSNR Variations
0
10
20
30
40
50
60
im
age1.bm
p
im
age2.bm
p
im
age3.bm
p
im
age4.bm
p
im
age5.bm
p
PSNR Value using Median
filter
PSNR Value using DWT
Filter
PSNR Value using
Watermark algorithm

VII. Conclusion
In this paper, an effective watermarking
scheme is presented and implemented on the database
containing satellite images. The proposed frequency
domain watermarking scheme made use of hybrid
approach, in which Discrete Cosine Transform is
combined with Daubechies 4 wavelet transform. It is
concluded that the MSE, RMSE and PSNR results
produced by the hybrid approach (DCT-DWT) for
watermarking gives enhanced results than the results
produced when median filter is applied and analysis
done when DWT is applied alone. As future work,
various other methods such as LSB method, MSB
block based methods may be used in hybrid approach
with discrete wavelet transform to either embed or
extract a watermark or both.
References
[1] DWT-SVD based secured image
watermarking for copyright protection using
visual cryptography, CSIT,2012 Sushila
Kamble, Vikas Maheshkar , Suneeta
Agarwal , Vinay K Srivastava, Department
of Computer science & Engineering,
MNNIT, Allahabad, India
[2] Digital Security using Watermarking
Techniques via Discrete Wavelet Transform
National Conference on Security Issues in
Network Technologies (NCSI-2012)
August, 2012
[3] Watermark Logo in Digital Image using
DWT Proceedings of SPIT-IEEE
Colloquium and International Conference,
Mumbai, India
[4] Comparative Study of DWT and DWT-SVD
Image Watermarking Techniques
International Journal of Advanced Research
in Computer Science and Software
Engineering, Volume 3, Issue 6, June 2013
[5] UML Modeling for the Watermarking
Image File Using Transform Method
International Journal of Advanced Research
in Computer Science, Volume 4, No. 8,
May- June 2013
[6] Study on high Performance and Effective
Watermarking Scheme using Hybrid
Transform International Journal on Recent
and Innovation Trends in Computing and
Communication ISSN 2321 – 8169
Volume: 1 Issue: 3, IJRITCC March 2013.
[7] A. Piva, F. Bartolini, and M. Barni,
“Managing copyright in open networks,”
IEEE Transactions on Internet Computing,
Vol. 6, No. 3, pp. 18–26, May–Jun. 2002.
[8] C. Lu, H. Yuan, and M. Liao, “Multipurpose
watermarking for image authentication and
protection,” IEEE Transactions on Image
Processing, Vol. 10, No.10, pp. 1579–1592,
Oct. 2001.
[9] Tosihiro Akiyama, Fumiaki Motoyoshi,
Osamu Uchida and Shohachiro Nakanishi,
"Hybrid Digital Watermarking For Color
Images Based On Wavelet
Transform",2006.
[10] Memon, N. and Wong, P., “Protecting
Digital Media Content” In: Communications
of ACM, Volume. 41, No. 7, pp. 35-43, July
1998.
[11] G. Voyatzis and I. Pitas, “The use of
watermarks in the protection of digital
multimedia products," IEEE Proceedings,
Vol. 87, No. 7, pp 1197-1207, July 1999.
[12] Liu Yongliang1, Xiaolin Yang1, Hongxun
Yao1, Tiejun Huang2, Wen Gao2,
“Watermark Detection Schemes with High
Security”, Proceedings of the International
Conference on Information Technology:
Coding and Computing (ITCC’05) IEEE.
[13] Shin- Hao and Yuan-Pei” Wavelet Tree
Quantization For Copyright Protection
Watermarking”, IEEE Transaction On IP,
Vol13, No.2, Feb-2004
[14] A. Umaamaheshvari and Dr. K.
Thanushkodi,” An Effective Watermarking
Scheme for Medical Images Using Hybrid
Transform (DCT- DWT) vol.5 no (1-4).
2011 in IJCSES.
[15] Xiangbin Feng, Yonghong Chen, College of
Computer Science & Technology, Huaqiao
University, Xiamen, China, Digital Image
Watermarking Based on Super- Resolution
Image Reconstruction, 9th International
Conference on Fuzzy Systems and
Knowledge Discovery,2012.

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