Hybrid Digital Image Watermarking Technique for Data Hiding

30th NATIONAL RADIO SCIENCE CONFERENCE (NRSC 2013)

April 16-18, 2013, National Telecommunication Institute, Egypt

ell. Hybrid Digital Image Watermarking Technique for Data Hiding

Ezz El-Din Hemdan1, Nawal El-Fishaw/, Gamal Attiya1, Fathi Abd El-Samii

1 Computer Science and Engineering Dept., Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt. 2 Electronics and Electrical Comm. Eng. Dept., Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.

E-mails: [email protected]@[email protected] and [email protected]

ABSTRACT:

This paper presents a hybrid image watermarking technique for data hiding over Internet. The idea of the

proposed technique is based on fusing multiple watermark images using wavelet fusion algorithm. Then, the

resultant fused watermark is embedded in the original image using hybrid DWT-SVD watermarking algorithm to

produce the watermarked image. The performance of the proposed algorithm is evaluated and a comparative study

is done between the hybrid DWT-SVD and SVD watermarking algorithm for single and multiple watermarks. The

experimental results verify and prove that the wavelet fusion is an efficient algorithm for fusing multiple

watermarks. The image watermarking technique using the hybrid DWT-SVD is more robust than that using the

SVD only. The results also prove that the proposed watermarking technique improves both the capacity of the

embedded information and robustness without affecting the perceptual quality of the original image. Indeed, the

extraction of the fused watermark is possible in the presence of severe attacks.

Keywords: Data Hiding, Digital Watermarking, Wavelet Fusion, Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD).

I. INTRODUCTION:

Recently, the Internet becomes the most important media for information and data communication such as image, audio and video. However, some safety tools should be used to protect the transmission of critical data over the Internet. There has been growing interest in developing techniques to protect data transmission such as encryption and data hiding. An importance sub-discipline of data hiding is called digital watermarking. Digital watermarking is the process of embedding a watermark in a multimedia object. This object may be image, audio, video and any digital content for the purpose of information hiding [1]. Many applications such as E-commerce, E-voting, copyright protection, content authentication, medical safety, broadcasting monitoring, military and indexing can be protected by digital watermarking [2].

Several algorithms have been proposed for watermarking, especially for image watermarking [3]-[6]. In [3], the authors proposed a robust blind digital image watermarking method based on singular value decomposition in wavelet domain to proof of ownership. In [4], a multi-watermarking scheme is proposed by embedding three independent binary watermarks in a grayscale digital image. In [5], a block based digital image watermarking

algorithm is developed based on Singular Value Decomposition (SVD) mathematical technique. In [6], a multiple watermarking technique for e-commerce is introduced based on Discrete Wavelet Transform (DWT).

Although several algorithms are developed for digital image watermarking to achieve data hiding, a problem arises is that as the capacity of embedded information increases, the quality of the watermarked image and the robustness against attacks are decreased. Therefore, many challenges to design a robust watermarking algorithm are posed due to conflicting of watermarking algorithm characteristics as imperceptibility, robustness, capacity and security [7]. Hence, there is a need for developing a robust image watermarking algorithm with ability to embed multiple watermarks without affecting the perceptual quality of the original image.

In this paper, a hybrid digital image watermarking technique is developed for data hiding taking into account increasing capacity without affecting the quality of the watermarked image. In the proposed technique, multiple watermarks images are first fused using wavelet fusion. Then, the resultant fused watermark is embedded in the original image using the hybrid DWT-SVD watermarking algorithm to produce the watermarked image.

978-1-4673-6222-1/13/$31.00 mOl3 IEEE 220



The rest of the paper is organized as follows. Section II provides basic design principles of an image watermarking algorithm. Section III introduces the digital watermarking life cycle while the proposed technique is described in Section TV. Section V describes the proposed algorithm while Section VI presents the experimental results of applying the proposed technique on some images while the paper conclusion is presented in Section VIT.

II. DESIGNING PRINCIPLES OF IMAGE WATERMARKING ALGORITHM

Image watermarking algorithm should have the following characteristics [2]: I. TmperceptibiJity: the watermarked image should be not affect the quality of the original image, thus it

should be invisible for human eye. 2. Robustness: the watermarked image should not be removed or eliminated by unauthorized person, thus it

should resist modifications by attacks. 3. Capacity: the number of bits that can be embedded in the host signal. 4. Security: the watermark should only be detected by authorized person.

All these characteristics are often contradictory with each other and must make trade-off between them to produce a robust watermarking algorithm.

III. DIGITAL WATERMARKING LIFE CYCLE

The life cycle of digital watermarking is shown in Figure 1. The watermarking technique consists of three steps [8]:

1. Embedding: an algorithm accepts the host and the data to be embedded, and produces a watermarked signal. Then, the watermarked digital signal is transmitted to another person or stored.

2. Attack: unauthorized person try to make modifications. 3. 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 still is present and it may be extracted.

IV. PROPOSED TECHNIQUE

Secure Part

, ,

-� ... -.. -- -....

Detecting Retrieval Function

DR

Fig. I: Digital watennarkin g l ife-cy cl e [8].

Result�

The proposed hybrid image watermarking technique consists of two phases as shown in Figure 2. In the first phase, the primary watermark is fused with the secondary watermark using wavelet fusion to produce fused watermark. In the second phase, the fused watermark is embedded in the original image using the hybrid DWTSVD watermarking algorithm. On the other hand, the extraction process occurs in two steps; the extraction of fused image and the extraction of both the primary and the secondary watermarks .

............................................................................................................ ···························_··_··_·_· r················ ..................................................................................................... ,

Primary Watennark Original Image

Secondary Watennark Fused Watennark Watennarked Image

Phase 1 Phase 2 ............................................................... ...................... _ .... _ ... _ ... _ .... _ .... _---,---.,-------'

Fig. 2: Proposed Technique.

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Phase 1: Wavelet Based Image Fusion

Wavelet based fusion is an effective technique for combining perceptually important image features which used for many applications such as medical applications and remote sensing applications [9]-[ 11]. Two images are first transformed using wavelet transform. Then, the fusion is done and finally the inverse wavelet transform IS computed to construct the fused image. This process is shown in Figure 3.

Tmage I ---+[ DWT •

Fusion H IDWT }---+ Fused Tmage

Tmage 2 ---+[ DWT f

Fig. 3: Wavelet Fusion of Two Images.

Phase 2: Embedding using Hybrid DWT-SVD Watermarking Algorithm

1) DWT Watermarking Algorithm

The Discrete Wavelet Transform (DWT) is currently used to in a wide variety of signal processing applications such as image, audio and video compression and removal of noise in audio. Here one-dimensional DWT separates an image into four bands of data denoted by Lower Level (LL) resolution approximation image, Horizontal Level (HL), Vertical (LH) and Diagonal (HH) detail components [12], As shown below in Figure 4.

LL HL

LH HH

Fig. 4: One-level DWT.

2) SVD Watermarking Algorithm

T he Singular V alue Decomposition (SVD) is mathematical technique. The main properties of SVD from viewpoint of image processing are the singular V alues (SVs) of image which:

1. Have a good stability when small perturbation is added to an image, its SVs do not change significantly which robust against different attacks.

2. Represent intrinsic algebra properties of image. Using these properties, the watermark can be embedded to SVD matrix without large variation In the

watermarked image which robust against many types attacks [13]-[16].

3) Why Hybrid DWT-SVD Watermarking Algorithm?

Spatial domain has many disadvantages that do not allow for the exploitation of this subsequent processing in order to increase the robustness of the watermark. It is generally preferable to hide watermarking information in noisy regions and edges of image, rather than in smoother regions. The benefits is two-fold; (1) degradation in smooth regions of an image is more noticeable to Human Visual Technique (HVS), and (2) becomes a prime target for lossy compression. Thus, working in transform domain becomes more attractive [7]. Therefore many techniques are used for image watermarking such as, Discrete Wavelet Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD) and Least Significant bit (LSB).

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v. ALGORITHM DESCRIPTION

A. Watermarking Embedding Algorithm

The watermarking embedding algorithm is shown in Figure 5. The algorithm works as follows: 1. The original image is transformed into four sub-bands using the one-level DWT. 2. The SVD is performed on the A matrix.

A = US VT (1) 3. The primary and secondary watermarks are fused using wavelet fusion. 4. The W matrix (fused image) is added to the SVs of the A matrix.

D = S + a W (2) To keep the image undistorted, small value of a is chosen (0.01)

5. The SVD is performed on the new modified (D matrix). D = Uw SIr VT" (3)

6. The Aw matrix (watermarked image) is obtained using matrix Sw. A,,=U SIr VT (4)

7. The watermarked image is inversed using the one-levellDWT.

[ Primary Watermark

+ [ Secondary \Vatermark ]-"1 Fusion

Original Image Watermarked Image

u,v

Fig. 5: Multiple Watermarking Embedding Strategy .

B. Watermarking Extracting Algorithm

The watermarking extracting algorithm is shown in Figure 6. The algorithm works as follows: 1. The watermarked image is transformed using the one-level D WT. 2. The SVD is performed on the A

*w matrix (watermarked image).

A*" = U* S*w V*T (5)

3. The matrix includes the fused image is computed. * * l' D = u'v S lV V 11' (6)

4. The possibly fused watermark is obtained. W* = (D*- S)/ a (7)

5. Anti-fusion of the fused watermark using wavelet fusion to extract primary and secondary watermarks. 6. The correlation coefficient between the fused watermark and the extracted one is estimated. 7. The correlation coefficient between the primary, secondary watermarks and the extracted ones is estimated.

[ Watermarked Image H DWT H SVD 1

�S\<

s

Extracted Primary Watermark

Extracted Secondary \Vatermark

Fig. 6: Multiple Watermarking Extracting Strategy .

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VI. EXPERIMENTAL STUDY

A. Simulation Environment

The proposed hybrid image watermarking technique is coded using MATLAB on Intel(R) Core(TM) i3 CPU with 20B RAM running Windows 7 and several experiments are carried out to evaluate the proposed technique. The wavelet fusion is applied on 256 x 256 logo image as primary watermark and on 256 x 256 Lena image as secondary watermark to produce the fused watermark. The hybrid DWT-SVD watermarking techniques are used for embedding the fused watermark in the 256 x 256 cameraman image as the original image. Tn all experiments, the quality of the watermarked image is evaluated by applying Peak Signal to Noise Ratio (PSNR) and the correlation coefficient (Cr) as image quality metrics.

B. Quality Metrics

The proposed hybrid image watermarking technique has two main objectives; hiding the fused image in the original image and maintaining the perceptual quality of the watermarked image. Here, are used Peak Signal to Noise Ratio (PSNR) and Correlation Coefficient (Cr) to measure the quality of images [17].

1) Peak Signal to Noise Ratio (PSNR)

The quality of watermarked image is measured in terms of PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error). Tn ideal case, PSNR should be infinite and MSE should be zero. But this is not possible for watermarked image, so large PSNR and small MSE is desirable.

MSE = In::. In_ (ORG(i,j)-WM(i,j)) l-l J-l m*n

PSNR = lOla (max-max)

g10 MSE Where: m and n are the size of original image and max=255

(WM): watermarked image.

2) Correlation Coefficient (Cr)

(8)

(9)

for grey image, (ORO): original image,

The closeness between the original image and the modified one is measured by the correlation coefficient (Cr). In ideal case the Cr should be one. But this is not possible for the extracted fused image, so the close value to one is desirable.

c, = LmLn(Xi-X')(Yi-Y,)

(10) J (Lm Ln(Xi -x')2)(Lm Ln(Yi _ y,)2)

Where: X' is the average value of the original image and Y' is the average value of the modified image.

c. Results

To illustrate the validity and performance of the proposed technique the experimental results are presented in this section, many results carried out under different original images but due to the limited space, only the cameraman image used as the original image.

Figures 7, 8 and 9 show the experimental results. Figure 7 shows the original and the extracted images watermarked, primary, secondary and fused the watermarks which are used in the experimental study. The correlation coefficient of extracted watermarks without attack is equal one i.e. perfectly extraction of the watermark.

Table 1 presents the PSNR in dB for SVD and hybrid DWT_SVD watermarking algorithm for single and multiple watermarks. The results show that proposed watermarking technique improves both the capacity of the embedded information and robustness without affecting the perceptual quality of the original image

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(S (a) Original Image (c) Primary Watermark (e) Secondary Watermark

(S (b) Watermarked Image (d) Extracted Primary (t) Extracted Secondary

Watermark( Cr1=1) Watermark( Cr2=1) Fig. 7: Watermarked Image without Attack (PSNR=64.3155).

(g) Fused Watermark

(h) Extracted Fused Watermark( Cr=l)

The experimental results show that the proposed technique is independent of the type of image used as the original image as shown in figure 8.

(a) Peppers

PSNR=61.6617

Cr=l Cr1=1 Cr2=1

(b) Mandi

PSNR =61.4618

(c) Pout

PSNR=58.2885

Cr1=1 Cr1=1 Cr2=1 Cr2=1

Fig. 8: Different Images for Testing.

(d) Onion

PSNR=60.6508

Cr=l Cr1=1 Cr2=1

Figure 9 shows the watermarked image and extracted watermarks after applying Gaussian noise, filtering and cropping attacks on the watermarked image respectively.

n ( a) Watermarked Image (b) Extracted Primary (c) Extracted Secondary

Watermark( Cr1=0.9371) Watermark( Cr2=0.5124)

Gaussian Noise (0.01) Attack

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(d) Extracted Fused

Watermark(Cr=0.8180)



(e) Watermarked Image (f) Extracted Primary (g) Extracted Secondary

Watennark(Cr1=O.3153) Watennark( Cr2=O.1360)

Filtering Attack

(i) Watermarked Image G) Extracted Primary (k) Extracted Secondary

Watermark( Cr1=O.5961) Watennark( Cr2=O.2529) Cropping Attack

(h) Extracted Fused

Watermark(Cr=O.3099)

(I) Extracted Fused

Watennark( Cr=O.5479)

Fig. 9: Watermarked Image with Gaussian Noise, Fil tering and Cropping Attacks.

Tabl e I: Comparison Study

� SVD only with DWT-SVD with SVD only with Proposed

Attack one watermark one watermark fused Technique

watermark

No Attack 60.5775 61.1391 63.8077 64.3155

Gaussian Noise 20.3733 20.4082 20.4040 20.4017

Filtering 20.6968 20.6968 20.6921 20.6928

Cropping 7.8124 7.8124 7.8116 7.8166

VII. CONCLUSIONS:

A hybrid image watermarking technique is proposed and evaluated using several test images. In the proposed

technique, two watermark images are first fused then the fused watermark is embedded using the DWT -SVD

watermarking algorithm. The experimental results show that, the proposed algorithm achieves higher degree of

capacity and robustness than traditional image watermarking algorithms without affecting image perceptual

quality. Also, the proposed technique using the hybrid DWT-SVD watermarking algorithm is suitable for the

extraction of the fused watermark even in the presence of attacks. Thus, the proposed image watermarking

technique can be used in different applications, depending on the used core watermarking algorithm. Also, the

proposed technique shows that the wavelet fusion can be used as a new way to embed more images in the

watermarking system.

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Hybrid Digital Image Watermarking Technique for Data Hiding

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