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\title{Robust Watermarking Method for Color Images Using DCT Coefficients of Watermark}
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\begin{document}

             \author[1]{Dr. R.  Eswaraiah}

             \author[2]{E.Sreenivasa  Reddy}

             \affil[1]{  Vasireddy Venkatadri Institute of Technology}

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\date{\small \em Received: 12 February 2012 Accepted: 3 March 2012 Published: 15 March 2012}

\maketitle


\begin{abstract}
        


Digital technologies are playing a vital role in the present communication system. This paper presents a robust and secure watermarking method to protect the copyright information of multimedia objects. In the proposed method, Discrete Wavelet Transform and Discrete Cosine Transform are applied on the cover image and then Discrete Cosine Transform coefficients of watermark image are embedded into transformed cover image. The experimental result shows the performance evaluation of the proposed method by the quality metrics as PSNR for watermarked image and NC for extracted watermark image and we have compared the results with the existing transformation methods in frequency domain based on attacks.

\end{abstract}


\keywords{Discrete Wavelet Transform (DWT);Discrete Cosine Transform (DCT);PSNR(Peak Signal to Noise Ratio);NC (Normalized Correlation)}

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\let\tabcellsep& 	 	 		 
\section[{INTRODUCTION}]{INTRODUCTION}\par
ow days the rapid growth of the technology is a cause for the requirement of the protection of copyright information from unauthorized access. Hence an advanced authentication method is essential to the data security. Digital watermarking is one such method that offers data security. At present various kinds of digital watermarking methods are in use to protect the information from unauthorized access. Any security method come under either spatial \hyperref[b0]{[1]} like LSB or frequency domain \hyperref[b1]{[2]} like Discrete Wavelet Transform (DWT) \hyperref[b4]{[5]}, Discrete Cosine Transform (DCT) \hyperref[b2]{[3]}, Discrete Fourier Transform (DFT) \hyperref[b5]{[6]} and the combination of them  {\ref [7,} {\ref 8]} as well as any method can come under either blind or non blind watermarking. In blind watermarking the cover image is not used to decipher the watermark \hyperref[b2]{[3]}. The cover image is used to decipher the watermark in the non-blind watermarking \hyperref[b3]{[4]}. This paper proposes a non blind watermarking method based on the frequency domain. This method uses the transformations to improve the robustness of the system. The necessary features are perceptual quality and robustness to determine the quality of watermarking scheme.\par
In the frequency domain, DWT decomposes an image into multi-resolution components i.e. horizontal, vertical and diagonal \hyperref[b4]{[5]} and DCT segregate each block into three frequency sub-bands: low, mid and high \hyperref[b2]{[3]}. DFT requires an input image that is discrete. Such inputs are often created by sampling a continuous function. But, in this correspondence, DWT-DCT combination  {\ref [7]} and DCT coefficients of watermark are used in the proposed method. It improves all security factors in the data transfer. The strength of this paper is, analysis of the proposed scheme based on the standard metrics such as PSNR and NC and it sustains the general attacks like Gaussian noise, salt \& pepper noise, Poisson noise, Gaussian blur, sharpening and common image processing operations like cropping, JPEG compression. The rest of the paper is organized in the following way. Section 2 consists of proposed method. Section 3 holds the description of performance metrics. Results and analysis are illustrated in Section 4. 
\section[{II.}]{II.} 
\section[{PROPOSED METHOD}]{PROPOSED METHOD}\par
The main aim of the proposed method is to improve the quality of watermarked image and robustness of the watermark. This approach consists of two major processes.\par
? Applying DWT and DCT on RGB cover image to get transformed image. ? Embed DCT coefficients of watermark image into transformed image. 
\section[{a) Watermark Embedding Algorithm}]{a) Watermark Embedding Algorithm}\par
In watermark embedding process, till now researchers are using either DWT or DCT or both transformations. Here, we are using both DWT and DCT to transform the cover image as transformed image and a new and efficient embedding algorithm which embeds DCT coefficients of watermark image into transformed image to get the watermarked image as shown in Fig 1  {\ref .} It is elucidated in the following way. 
\section[{Algorithm}]{Algorithm}\par
Step 1: Consider any color image as cover image denote it by 'I'. Get R, G, B channels of cover image 'I'.\par
Step 2: Apply DWT to blue channel 'B' to get the multi-resolution sub-bands LL1, HL1, LH1, and HH1. When compared to red and green channels blue channel is more resistant to changes.\par
Step 3: Apply DWT again to HL1 sub-band of B channel and choose HL2 sub-band.\par
Step 4: Divide the HL2 sub-band into blocks of size 8×8.\par
Step 5: Apply DCT to the blocks obtained in step 4.  Step 7: To embed the watermark, select any four coefficients in the mid frequency band of each DCT block of HL2 sub-band.\par
Step 8: Four DCT coefficients of watermark are stored in each DCT block of HL2 sub-band.\par
Step 9: The DC component from the DCT coefficients of watermark is normalized before embedding.\par
Step 10: Apply IDCT to the blocks of HL2 sub-band.\par
Step 11: Apply IDWT for 2 levels.\par
Step 12: Combine R, G, B channels to get watermarked image 'WI'.\par
It helps to improve the copyright protection of the cover image and robustness of the watermark in the watermarked image.  
\section[{PERFORMANCE EVALUATION METRICS}]{PERFORMANCE EVALUATION METRICS}\par
To measure the quality of the watermarked image peak signal to noise ratio (PSNR) is used. The quality of extracted watermark is measured using Normalized Correlation (NC) between the extracted and the original watermark.  
\section[{MSE}]{MSE}\par
Where n denotes the number of bits used for color representation and MSE refers to the Mean Square Error between original and water marked image and is calculated with the formula.MSE = ? ? ? (I[i, j] ? I ? [i, j]) 2 ?? ?? =1 ?? ??=1 ??,??,?? 
\section[{3MN}]{3MN}\par
Here, M and N are the height and width of image respectively. I[i, j] denotes the (i, j)th pixel value of the original image and I'[i, j] denotes the (i, j)th pixel value of watermarked image. 
\section[{b) Normalized Correlation (NC)}]{b) Normalized Correlation (NC)}\par
It is one of the metrics used to find the quality of extracted watermark image with respect to the original watermark image. It is found by using the following formula.NC = ? ? w(i, j)w ? (i, j) N j=1 M i=1 ?? ? w(i, j)\textasciicircum 2 N j=1 M i=1 ?? ? w ? (i, j)\textasciicircum 2 N j=1 M i=1\par
Here, w(i, j) is the original watermark, w'(i, j) is the extracted watermark.\par
IV. 
\section[{RESULTS AND ANALYSIS}]{RESULTS AND ANALYSIS}\par
As per this proposed method, a Lena color image of size 512×512 is considered as cover image as shown in Fig.  {\ref 3} and Fig.  {\ref 4} is a gray scale image of skeleton with size 32×32 is chosen as watermark. Step 2: Apply DWT to blue channel 'B' to get the multi-resolution sub-bands LL1, HL1, LH1, and HH1.\par
Step 3: Apply DWT again to HL1 sub-band of B channel and choose HL2 sub-band.\par
Step 4: Divide the HL2 sub-band into blocks of size 8×8.\par
Step 5: Apply DCT to the blocks obtained in step 4\par
Step 6: Obtain four DCT coefficients of watermark from the four selected coefficients of mid frequency band of each DCT of HL2 sub-band.\par
Step 7: To get the watermark apply IDCT on the set of DCT coefficients obtained from previous step.  
\section[{Table I : PSNR and NC values}]{Table I : PSNR and NC values}\par
Table  {\ref 2} shows comparison results of the proposed method with the existing transformation methods such as DWT \hyperref[b4]{[5]}, DWT-DCT [9] and Bior [10] based on the NC value between original and extracted watermark when the watermarked image undergoes any attacks. 
\section[{Table II : Comparison Results}]{Table II : Comparison Results}\par
This robust watermarking method is proposed for increasing the security of data hiding as well as quality compared with the existing algorithms. Authenticity is incorporated by embedding the DCT coefficients of watermark image into the transformed image. Experimental results based on attacks confirm that the proposed algorithm performs better than the DWT, DWT-DCT and Bior based scheme and robustness is achieved by hiding DCT coefficients of watermark image in transformed image by the frequency transformations as DWT and DCT.\begin{figure}[htbp]
\noindent\textbf{6}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Step 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-4.png}
\caption{\label{fig_2}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-5.png}
\caption{\label{fig_3}Figure 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{31}\includegraphics[]{image-6.png}
\caption{\label{fig_4}Figure 3 :Step 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5}\includegraphics[]{image-7.png}
\caption{\label{fig_5}Figure 5 :}\end{figure}
 		 		\backmatter   			 \par
We are very much thankful to the various reviewers who helped us to bring the paper effectively. The valuable suggestions of Dr. Ch.Rupa could not be underestimated in several situations of developing the paper. We sincerely thank our other research friends for giving their precious cautions. For the invaluable research facilities provided by the magnanimous management for achieving the work, we convey our deepest thanks. 			  			 			 			  				\begin{bibitemlist}{1}
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\bibitem[Chengqing et al.]{b5}\label{b5} 	 		‘A color image watermarking algorithm resistant to Print-Scan’.  		 			Guo Chengqing 		,  		 			Guoai Xu 		,  		 			Xinxin Niu 		,  		 			Yixian Yang 		,  		 			Yang Li 		.  	 	 		\textit{IEEE International}  		 	 
\bibitem[Cheng-Qun Yin et al. (2007)]{b4}\label{b4} 	 		‘Color image watermarking algorithm based on DWT-SVD’.  		 			Li Cheng-Qun Yin 		,  		 			An-Qiang Li 		,  		 			Li Lv 		,  		 			Qu 		.  	 	 		\textit{Proceedings of the IEEE International Conference on Automation and Logistics},  				 (the IEEE International Conference on Automation and Logistics)  		August 2007. p. .  	 
\bibitem[Dharwadkar and Gorai (2011)]{b3}\label{b3} 	 		‘Non-blind watermarking scheme for color images in RGB space using DWT-SVD’.  		 			N V Dharwadkar 		,  		 			Amberker B B Gorai 		,  		 			A 		.  	 	 		\textit{International Conference on Communications and Signal Processing},  				February 2011. p. .  	 
\bibitem[Mondal and Barik (2012)]{b0}\label{b0} 	 		‘Spatial domain robust watermarking scheme for color image’.  		 			Manik Mondal 		,  		 			Debalina Barik 		.  	 	 		\textit{International Journal of Advanced Computer Science}  		Jan 2012. 2  (1)  p. .  	 
\bibitem[Baisa et al. (2012)]{b1}\label{b1} 	 		‘Strongly robust and highly secured DWT-SVD based color image watermarking: embedding data in all Y, U, V color spaces’.  		 			L Baisa 		,  		 			Gunjal 		,  		 			N Suresh 		,  		 			Mali 		.  	 	 		\textit{I.J. Information Technology and Computer Science}  		April 2012. 3 p. .  	 
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\end{document}
