Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
A BALANCED SEMI-BLIND DIGITAL WATERMARKING SCHEME USING DWT The block diagram of the proposed watermarks embedding scheme is shown in Fig. 3.2. 3.1. Watermark Selection and Embedding In Discrete Wavelet Transformed image watermark (unique sequence of real numbers) has been embedded using coefficients that are near the largest coefficient (T1) value of those subbands of a given image. Since threshold values for watermark insertion are calculated from the given input image, and hence there is no need of predefined threshold. The following equation is used for watermark embedding. Xi = Xi + α| Xi |Wi (1) Where the Xi are all the significant DWT coefficients, such that i run over all DWT coefficients > T1. Wi is the watermark value at the position of Xi. Wi is generated from a uniform distribution of zero mean and unit variance. And is taken to be 0.4, 0.3, 0.2, and 0.1 respectively for each level of decomposition from 1st to 4th. Furthermore, more robustness can be achieved through two or three times embedding of the WM in the LH and HL sub-bands and selection of filter bank of DWT is another important factor to survive various attacks. From [30], we witnessed that Bior (4.4, 6.8) filter has potential features that can survive resizing and scaling factors. 3.2. Watermark Detection The most commonly used detector for watermarking schemes is the correlation detector [15, 26], which is optimal when data samples follow the Gaussian distribution function. In our proposed watermark detection algorithm we have implemented our detection function as a correlation detector. The correlation Z between the DWT coefficients X of the corrupted watermarked image and a possibly different watermark Y is computed as: (2) Where i run over all DWT coefficients >= T2 > T1 and M is the number of such coefficients, where T2 > T1+WM. The threshold S is defined as: (3) If Z exceeds S, the conclusion is presence of watermark. This process is repeated for both watermark WM1 and WM2 for buyers and Sellers. Any watermarked image is assumed to be identical to the original image as long as the PSNR value between original and watermarked image are kept at low difference. The PSNR is defined as: (4) where mean-square error (MSE) is defined as : (5) 93