Abstract :
In this paper, a state art of robust watermarking techniques was first presented, Print-scan resistant digital watermarking algorithm, used in the environment of print and scan, will be able to solve the issue of copyright protection in the printed works. The robustness of a perceptual watermarking scheme based on a PJND (Pyramidal Just Noticeable Difference) model. Desynchronization attack known to be one of the most serious threats for any watermarking system. To cope with this type of attacks, we have proposed an approach based on the SIFT (Scale Invariant Feature Transform) and our PJND model adapted for the DoG (Difference of Gaussians) representation. The idea is to use JND to determine the optimum strength for embedding the watermark to provide an invisible and robust watermarking scheme. The image is first decomposed into a multi-resolution representation using the pyramidal decomposition. Then, a perceptual model is proposed to compute the JND value for each pixel at each Laplacian level. This model takes into account three main characteristics of the Human Visual System (HVS), namely: contrast sensitivity, luminance adaptation and contrast masking. The performance of the proposed technique is evaluated in terms of transparency, using subjective and objective tests, and robustness to different attacks from global transformation (Rotation, Scaling, etc) to local transformation (StirMark), including Print-Scan and Print Screen.
Keywords :
Gaussian processes; copyright; feature extraction; image coding; image resolution; image watermarking; transforms; visual perception; DoG representation; HVS characteristics; JND value; PJND model; SIFT; StirMark; contrast masking; contrast sensitivity; desynchronization attack; difference of Gaussian representation; global transformation; human visual system characteristics; image copyright protection; image decomposition; local transformation; luminance adaptation; multiresolution representation; perceptual watermarking scheme; print screen; print-scan resistant digital watermarking algorithm; printed works; pyramidal decomposition; pyramidal just noticeable difference model; scale invariant feature transform; watermarking method robustness; Difference of Gaussians (DoG); Human Visual System (HVS); Print-Scan; Robustness; Watermarking;