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Journal of Software Engineering and Applications, 2013, 6, 58-61 doi:10.4236/jsea.2013.63b013 Published Online March 2013 (http://www.scirp.org/journal/jsea) Copyright © 2013 SciRes. JSEA A Watermarking Algorithm Based on Wavelet and Hadamard Transform for Color Image Hongshou Yan, Weimin Yang College of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha 410004, Hunan, China. Email: 165393586@qq.com, luan_yang@126.com Received 2013 ABSTRACT Digital image watermarking is a useful solution to the problem of information security, copyright and network secur ity. In this paper, we propose a watermarking algorithm for color image based HT and DWT. A binary image as watermark is embedded into green component or blue component of color image. The algorithm can satisfy the transparence and robustness of the watermarking system very well. The experiment based on this algorithm demonstrates that the water- marking is robust to the common signal processing techniques including JPEG compressing, adding noise, low pass filter, and mosaic. Keywords: Digital Watermarking; Hadamard Transform(HT); Discrete Wavelet Transform(DWT); Color Image; Copyright Protection 1. Introduction Today, as the digitization develops day by day, the pro- tection of digital information becomes an urgent problem. In order to resist different kinds of infringement, a new technology that called watermarking had been put for- ward to in the international scope. Watermark is se- quence carrying information about the copyright owner to embed into th e digital image [1], audios and vid eos in order that owners can read it out while unauthorized us- ers cannot1 easily remove it. There are many methods to embed the watermark. It can be divided into two classes: spatial-domain water- marks and transform-domain watermarks. The spatial domain is so simple that the watermark can be damaged easily, but the transform-domain algorithm can be resist intensity attack, watermark information can’t be dam- aged easily. The transform algorithm includes chiefly DWT, DFT and DCT[2,3,4]. Wavelet transform is supe- rior to time-frequency transform for its inner predomi- nance. For example, wavelet has the character of multi-resolution, which can avoid the rectangle brought by DCT. In fact, it has more application fields in engi- neering and computer science. In this paper, a new blind watermarking algorithm that embeds a meaningful binary image into the color images is proposed based HT-DWT according to HT and DWT characteristics. The rest of the paper is organized as follows. Section 2 introduces the hadamard transform and discrete wavelet transforms analysis in briefly. In section 3, a new blind watermark algorithm for color image based HT-DWT domain is presented in detail. Experimental results are described in section 4. Finally, in section 5 the conclu- sion is given. 2. Watermark Embedding Principles 2.1. Hadamard Transform Analysis Hadamard transform by two values, namely 1 and -1,as a basic function expand made that it satisfies the complete orthogonal. Hadamard function is binary orthogonal functional corresponding to the two states in digital logic, and therefore more suitable for image processing hard- ware to achieve a faster rate than other transform. It has been widely used in the area of image processing and image compression. Dimensional discrete Hadamard transform positive transform and inverse transform, such as the definition of formula (1) and (2) [5]: 1 0 11 (()() ()()) 00 1 (,)(, )(1) N ii ii i NN bxbu bybv xy Huvf xy N (1) 1 0 11 (()() ()()) 00 1 (, )(,)(1) N ii ii i NN bxbu bybv uv fxy Huv N (2) (0,0)H is called image block the DC component ha- damard transform domain. Using an interactive relation- ship can generate higher order transform matrix of Ha- A Watermarking Algorithm Based on Wavelet and Hadamard Transform for Color Image Copyright © 2013 SciRes. JSEA 59 damard transform ,such as the formula (3) below. 122 2222 11 ,,1,2,3,... 1 kk k kk HH HH k HH (3) 2.2. Discret Wavelet Transform Principles Wavelet transform is a time-frequency domain combined analysis method. It has multi—resolution analysis fea- tures. Each level of the wavelet decomposition has four sub-images with same size. Let the k LL stands for the approximation sub-image and k LH , k H L, k H Hstand for the horizontal, vertical and diagonal direction high- frequency detail sub-image respectively. Where the variable 1,2,3,...( )kkN is the scale or the level of the wavelet decomposition. After wavelet decomposition, many signal processing, such as compression and filter are likely to change the high-frequency wavelet coefficients. If the watermark sequence is embedded into this part, its information may be lost in the processing in sequence, which will reduce the robustness of the watermark [3]. In order to ensure the watermark has a better imperceptibility and robust- ness, the approximation sub-image 3 LL coefficients are chosen to embed watermark. We can achieve the trans- form of the separable wavelet as in Figure 1. 3. Proposed Watermarking Algorithm Here, the readable watermark is a qq binary image. We arrange the binary image to 0, 1 watermark sequence wm. And the length of wm is the pq. Original image is a mn color image. 3.1. Watermark Embedding Scheme Step1 `A one-dimension chaotic sequence is originated from a logistic mapping 1(1 ) nnn X uX X [4]. The sequence has the same size as the length of the wm. Ap- ply a threshold value, and then get 0-1 sequences A*. The program performs a X OR operation of this wm with the binary watermark image. 0 X and u are pass- word. The sequence of the binary watermark image after encrypting is: LL3 LH3 HL3 HH3 LH2 HL2 HH2 LH1 HL1 HH1 Figure 1. Three level wavelet decomposition. (*,){() {0,1}|1}WXORAwmwii pq (4) Step2 Extracting the green components (G) and the from original color image. It is divided into square blocks of size 88 pixels. Then the HT is applied in each block. Then the DC value ,(1,1) ij H of each block is collected together to get a new matrix I . 1, 111, 1 1,1 1,2 2,12,22, 1 12, 1 21121,221,1121,1 2,12,22, 112, 1 (1,1)(1,1) ...(1,1)(1,1) (1,1)(1,1) ...(1,1)(1,1) ...... ......... , (1,1)(1,1)...(1,1)(1,1) (1,1)(1,1) ...(1,1) kk kk kk kkkk kkkk kk HHHH HHH H I HHH H HHHH (1,1) (5) where, 1/8,2 /8knk m Step3 Make the new matrix I to do a one-scale two-dimension discrete wavelet transform with haar. According to quantization step value s, make the low coefficient LL to qualified adjustment, then embed the watermark value. The detailed process is as follows: The quantified value (, )qi j of the low-frequency wavelet coefficient can be obtained by : (, )(, )/qi jLLi js (6) The process of embedding watermark information is as follows: If mod((,),2)()qi jWk , adjust the low-frequency wavelet coefficient to 2/),(),(' ssjiqjiLL (7) If mod( (,),2)()qi jWk , adjust the low-frequency wavelet coefficient to If (,)(, )(0,/2)LLijqi jss then '( ,)(( ,)1)/2LLijq ijss else '(,)((,) 1)/2LLijq ijss where, 1,2,...,/16,1,2,..., /16imjn , 1, 2, 3, ...,kpq. Step 4 Make wavelet inverse transform. Step 5 The (1,1) ij H of each block can be obtained by extracting the corresponding value the wavelet inverse- transform matrix, then make HT inverse-transform each sub-block. Chan ging the double-precision real number to unsigned 8-bit integer. Thus, obtain the color compo- nents in which watermark are embedded. Finally, we transform the image from three-basic-color image into true color RGB space. Then we will get the watermarked color image. 3.2. Watermark Extracting Scheme The processes of watermark extracting and embedding are reverse. When extracting watermark, the detailed ways is as follows: Step1 Extracting the green components (G), it is di- vided into 88 sub-block. Then the HT is applied in each block. Then the DC value ,(1,1) ij H of each block A Watermarking Algorithm Based on Wavelet and Hadamard Transform for Color Image Copyright © 2013 SciRes. JSEA 60 is collected together to get a new matrix ' I . 1,2,...,/8,1,2,..., /8imjn. 1,11,21, 111, 1 2,12,22, 1 12,1 2 1121,22 1, 112 1, 1 2,1 2,22 ' (1,1)'(1,1)...'(1,1)'(1,1) ' (1,1)'(1,1)...'(1,1)'(1,1) ...... ......... ' ',(1,1)'(1,1)...'(1,1)'(1,1) '(1,1) '(1,1)... kk kk kkkk kk kk kk HHH H HHH H I HHH H HH H ,11 2,1 (1,1)' (1,1) kkk H (8) where, 1/8,2 /8knk m . Step2 Make the matrix ' I to do a one-scale two-dimension discrete wavelet transform with haar, and extract the watermark from low-frequency wavelet coef- ficient LL. The detailed way is as follows: (, )(,)/qi jLLi js (9) '( )mod( (,),2)Wk qij (10) where, 1,2,...,/16,1,2,..., /16imjn, 1,2,3,...,kpq. The word s refers to quantization step value, and '( )Wk refers to extracted watermark sequences. Step3 The watermark sequences which is extracted carry on chaotically decryption. Then it can be trans- formed into a binary image. Here we use the normalized correlation (NC) to meas- ure the similarity between original image W and the detected watermark image 'W [6]. 11 11 (, )'(, ) (, )(, ) nn IJ NN ij WijW ij NC Wij Wij (11) In order to get rid of the impact of subjective factor, this paper adopts peak signal-to-noise ratio (PSNR) to measure the fidelity between the original image and the image which watermark is embedded. 4. Experiment Results In this paper, 400 512 3 true color lena image and baboon image are selected as the original image and a 20 40 binary image is selected as the watermark im- age. Lena image is embedded watermark in the blue components after contrasting the green components with the blue components. The quantization step value s is 106 in lena image. Watermark image is embedded into the blue compo- nents of lena image. The PSNR value of watermarked image (Figure 2(c)) is 42.05, the NC value of extracted watermark (Figure 2(d)) is 1.0. From Figure 2, the hu- man eye may feel no difference between the original im- age and the watermarked image. The algorithm can sat- isfy the transparence. In order to investigate the robustness of the water- marking scheme, the watermarked image was attacked by various signals processing technique, such as JPEG compression, Additive gaussian noise, Additive salt noise, Median filtering, image enhancement, mosaic and other kinds of image processing approaches to attack the watermarked image. Table 1 show the results of our simulations and Figure 3 shows that it be extracted wa- termark from being attacked watermarked lena image. (a) (b) (c) (d) Figure 2. (a) original lena image ; (b) original watermark ; (c) watermarked image; (d) extracted watermark. Table 1. Test results of watermarked image. lena Test Methodparameter PSNR NC Q=80 32.68 1.0000 Q=50 31.23 0.9936 JPEG compression Q=30 30.01 0.9488 Salt&pepper 1% 26.06 0.9981 Salt&pepper 2% 23.15 0.9855 Speckle noise 0.02 22.41 0.9976 Noise adding Gaussian noise 0.01 21.19 0.9617 Gaussian lowpass (3×3) 32.01 1.0000 Median filtering (2×2) 28.62 0.9272Filtering Median filtering (3×3) 31.84 0.9939 Edge sharppen 28.72 1.0000 Gaussian blurring 31.80 1.0000 image enhancement Moving blurring 27.10 0.9607 2×2 31.36 1.0000 3×3 28.04 1.0000Image mosaic 4×4 27.18 1.0000 A Watermarking Algorithm Based on Wavelet and Hadamard Transform for Color Image Copyright © 2013 SciRes. JSEA 61 (a) (b) (c) (d) (e) Figure 3. (a) JPEG compression Q=30; (b) Salt &pepper noise 2%; (c) Gaussian noise 0.01; (d) Median filtering 2×2; (e) Moving blurring. 5. Conclusions In this paper, a new blind technique for embedding a binary image into color digital image based on HT and DWT has been propo sed, which is robu st to the common signal processing techniques including JPEG compress- ing, noise, low pass filter, median filter, image enhance and mosaic. The algorithm is not only simply but also valid. This blind watermarking algorithm can broaden its application area. 6. Acknowledgment This work was supported by the Science and technology projects in Hunan Province(No.2010TZ4012) REFERENCES [1] I.J.Cox, J.Kilian, F.T.Leighton, and T.Shamoon, “Secure spread spectrum watermarking for multimedia”, IEEE Trans. Image Processing , vol .6, pp. 1673-1687, Decem- ber 1997. [2] G.Langelaarand, R.Lagendijk, “Optimal differential en- ergy watermarking of DCT encoded images and video”, IEEE Trans., vol .10,pp.148-158,January 2001. [3] J.W.Huang, Yun Q.SHI, W.D.Cheng, “Image water- marking in DCT: an embedding strategy and algorithm” ,Journal of Electronic, vol .28,pp.57-60, April 2000 [4] Z.M.Zhang, L.Wang, “Semiblind image watermarking algorithm in DCT domain with chaotic encryption”, Computer Engineering, vol.29,pp. 9-11, October 2003. [5] Pankaj U.Lande, Sanjay N.Talbar., “FPGA Implementa- tion of Adaptive Watermarking Using Human Visual Model”,.ICGST-PDCS Journal, vol.9,pp.17-21,January 2009 [6] L.C.Li, Z.Y.Lu, “Desynchronization attack on digital watermarks and their counte measures,” Journal of image and graphics, vol .10,pp.403-409, October 2005. |