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Dinesh Kumar and Vijay Chahar Digital Image Watermarking: A Review of SVD, DCT and DWT Based Approaches 30 sharping, transform, rescaling and Gamma Correction. The first attack applied is Gaussian Noise with zero mean and 0.5 variance. The second attack is rotation by 30 degree and 75 degree. The next image manipulation is cropping. We use a part of the image by selecting 50 % of the original size at the center and cropping every other pixel. The fourth attack is blurring using low pass filter of 3 × 3 window size. The fifth attack is median filtering. The sixth attack is histogram equalization. The seventh attack is image sharping. Next attack we applied on the watermark image is transform. The ninth attack is rescaling, the watermarked image was scaled from 256 × 256 to 128 × 128, and then rescaled to its original size. Lastly, we perform gamma correction attack that changes the brightness of pixels of the watermarked image by a specified factor 1.5. Correlation metric has been used for comparison between original watermark and extracted watermark after applying attacks on watermarked image. Figure 2 depicts the attacked images.The watermarks extracted from Peppers and Barbara images using proposed scheme are as shown in Figures 3 and 4 respectively. Figure 3: Extracted watermarks from Peppers as cover image and Logo as a watermark image using Proposed Method; (a) Gaussian Noise (b) Rotate 30 (c) Cropping (Left Half) (d) Median Filtering (e) Histogram (f) Sharpning (g) Resize (h) Gamma Correction (i) Transform Figure 2: Attacked images; (a) Gaussian Noise (b) Rotate 30 (c) Cropping (Left Half) (d) Median Filtering (e) Histogram (f) Sharpning (g) Resize (h) Gamma Correction (i) Transform Correlation coefficients corresponding to images i.e., Barbara and Lena as cover images and logo as a watermark image are given in Tables 1 and 2 respectively. Tables 3 and 4 show the correlation coefficients corresponding to images i.e., Peppers and Baboon as cover images and bird as a watermark image respectively.Prop stands for proposed method in all the tables. Figure 4: Extracted watermarks from Barbara as cover image and Bird as a watermark image using Proposed Method; (a) Gaussian Noise (b) Rotate 30 (c) Cropping (Left Half) (d) Median Filtering (e) Histogram (f) Sharpning (g) Resize (h) Gamma Correction (i) Transform INFOCOMP, v. 10, no. 3, p. 25-35, September of 2011.
Dinesh Kumar and Vijay Chahar Digital Image Watermarking: A Review of SVD, DCT and DWT Based Approaches 31 Table 1: Correlation coefficients for Barbara image as cover image and logo image as watermark Table 4: Correlation coefficients for Baboon image as cover image and Bird image as watermark Attacks Liu Gha Emir Haq Mis P rop G.Noise 0.61 0.68 0.57 0.58 0.72 0.76 G.Blur 0.86 0.92 0.96 0.96 0.94 0.96 Crop(R.H) 0.60 0.97 0.95 0.91 0.94 0.99 Crop(L.H) 0.49 0.97 0.88 0.95 0.88 0.98 Rotate30 0.64 0.79 0.54 0.62 0.87 0.93 Rotate75 0.75 0.80 0.52 0.70 0.87 0.91 Mid.F il. 0.94 0.94 0.97 0.98 0.95 0.97 Hist.Eq. 0.88 0.90 0.99 0.99 0.99 0.99 Sharp 0.75 0.82 0.89 0.89 0.88 0.96 T rans 0.87 0.90 0.60 0.71 0.86 0.97 Resize 0.99 0.99 0.85 0.92 0.92 0.89 G.Corr 0.96 0.98 0.99 0.99 0.99 0.99 Attacks Liu Gha Emir Haq Mis P rop G.Noise 0.57 0.65 0.58 0.57 0.65 0.69 G.Blur 0.73 0.80 0.83 0.80 0.85 0.86 Crop(R.H) 0.38 0.98 0.72 0.81 0.80 0.99 Crop(L.H) 0.33 0.98 0.66 0.74 0.77 0.99 Rotate30 0.40 0.49 0.54 0.52 0.62 0.69 Rotate75 0.50 0.70 0.58 0.58 0.61 0.71 Mid.F il. 0.74 0.78 0.89 0.88 0.86 0.89 Hist.Eq. 0.99 0.98 0.98 0.97 0.98 0.98 Sharp 0.45 0.64 0.81 0.80 0.75 0.85 T rans 0.66 0.78 0.60 0.61 0.66 0.87 Resize 0.89 0.93 0.75 0.79 0.65 0.79 G.Corr 0.75 0.76 0.98 0.98 0.96 0.99 Table 2: Correlation coefficients for Lena image as cover image and logo image as watermark Attacks Liu Gha Emir Haq Mis P rop G.Noise 0.40 0.51 0.55 0.44 0.52 0.59 G.Blur 0.97 0.97 0.98 0.96 0.97 0.99 Crop(R.H) 0.43 0.97 0.97 0.99 0.98 0.99 Crop(L.H) 0.67 0.98 0.97 0.96 0.96 0.99 Rotate30 0.62 0.75 0.61 0.63 0.82 0.83 Rotate75 0.74 0.83 0.59 0.66 0.81 0.87 Mid.F il. 0.98 0.99 0.99 0.98 0.98 0.99 Hist.Eq. 0.96 0.98 0.99 0.98 0.99 0.99 Sharp 0.86 0.91 0.95 0.92 0.96 0.97 T rans 0.86 0.89 0.71 0.75 0.83 0.92 Resize 0.99 0.99 0.89 0.96 0.94 0.92 G.Corr 0.96 0.96 0.99 0.97 0.99 0.99 Table 3: Correlation coefficients for Peppers image as cover image and Bird image as watermark Attacks Liu Gha Emir Haq Mis P rop G.Noise 0.53 0.60 0.53 0.53 0.58 0.63 G.Blur 0.91 0.93 0.95 0.86 0.92 0.96 Crop(R.H) 0.33 0.98 0.87 0.95 0.92 0.99 Crop(L.H) 0.36 0.95 0.89 0.92 0.93 0.97 Rotate30 0.41 0.48 0.51 0.53 0.58 0.66 Rotate75 0.56 0.61 0.51 0.57 0.56 0.75 Mid.F il. 0.95 0.95 0.97 0.97 0.95 0.98 Hist.Eq. 0.89 0.95 0.99 0.96 0.96 0.98 Sharp 0.69 0.82 0.90 0.84 0.88 0.91 T rans 0.68 0.71 0.55 0.66 0.62 0.90 Resize 0.96 0.98 0.84 0.86 0.85 0.86 G.Corr 0.78 0.78 0.99 0.98 0.99 0.99 These tables show the correlation coefficients between the original watermark and extracted watermark using Liu, Ghazy, Emir Ganic, Rafizul Haque, Majumder, and proposed method. Maximum value of correlation coefficients means more similarity between extracted watermark and original watermark. The correlation coefficients using proposed method for Gaussian noise, Gaussian blurring, cropping, sharping, transform and rotation are far better and for other attacks such as histogram equalization, gamma correction attacks, and there is slight improvement. The results reveal that proposed method outperforms the other ones for cropping, rotations, sharping, transform, blurring and noise attacks. For Gamma correction and histogram equalization attacks, the results obtained using other methods are more or less equal to those as obtained using proposed method. In case of median filtering attack and gamma correction, Rafizul Haque and Majumder method performs better for one image (Barbara) respectively whereas for other images the proposed method gives good results though the difference is very little. In case of rescaling (or resizing) attack, Gahzy method gives better result as compared to other methods. For Peppers, Lena as cover images and bird as watermark image, Emir Ganic method performs better under histogram equalization attack. Next, we saw the effect of adding salt and peeper noise to watermarked images with densities within the interval [0.001, 0.09]. Tables 5 and 6 give correlation coefficients after applying salt and peeper noise attack for Barbara as cover images and logo and bird as watermark images. The results show that proposed method gives better results as the value of density increases. Another experiment was performed to see the effect of adding Gaussian noise to the watermarked image with different variance values using Barbara as cover images and bird and logo as watermark images and the results are tabulated in Tables 7 and 8. The results reveal that proposed method gives better results as the value of variance increases. But at low variance, other INFOCOMP, v. 10, no. 3, p. 25-35, September of 2011.
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