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An adaptive watermarking algorithm in the wavelet domain based on multi-scale morphological gradient is proposed in this paper. Using multi-scale morphological gradient, the distribution and the strength of the sub-block texture after the wavelet package decomposition are analyzed, and the textures of sub-blocks are sorted. According to the texture feature of the sub-block, the sub-block threshold is determined adaptively and the position which is bigger than its threshold is selected as the important coefficient position where the watermarking is embedded. Then, the strength of the position is modulated adaptively through noise visibility function (NVF), which is the best strength to ensure good visual effect of masking to achieve the best effect between robustness and imperceptibility. A large amount of experiments show that the proposed algorithm is effective and robust to common image processing operations.

An improved algorithm of Contour Initialization in GVF Snake Model is proposed in this paper based on detailed analysis of the problems in current active contour models: poor performance under interference, large computational cost, inability to converge to complex or rough contours and difficulty for setting initial contour, etc. Our method efficiently solved the problems in complex or rough contours initialization by connecting the initial points of different resolutions obtained by multi-scale edge detection methods based on wavelet transform and suitably controlling the number of GVF force field iterations. Experiments show that the initial contour can be accurately set close to the objective contour and successfully extract the objective contours with interferential edges and points. The new contour initialization algorithm has further reduced computational cost, improved the anti-jamming ability and extended the application range of GVF Snake model.