الفهرس | Only 14 pages are availabe for public view |
Abstract ABSTRACT Intelligent 3D Watermarking System and Applications By Mourad Raafat Mouhamed Mathematics Department, Faculty of Science, Helwan University The aim of this work was to propose an intelligent 3D watermarking system. Ultimately, a good watermark should satisfy some watermarking requirements, such as imperceptibility and robustness against attacks. The 3D watermarking techniques classified into three generation. The third-generation techniques add intelligent layer to the techniques wish used in the first and second generation. This intelligent layer help to solve the trade of between the two requirements of any watermarking system. In this work we proposed three watermarking approaches first one is novel robust and blind 3D watermarking approach that used the spherical coordinates of the vertices of the 3D mesh model to embed the watermark using a random table as a key to makes it more secure. Experimental results demonstrate that the proposed approach is giving pretty immeasurable imperceptibility compared with other techniques likewise is robust against different types of attacks, for example, Similarity transformation, cropping, subdivision, and simplification. Secondly, an intelligent phase added to this approach where the second approach presents a robust 3D mesh watermarking approach, that adopts an optimization method of selecting vertices from 3D mesh models, that will carry the watermark bitstream. The proposed watermark approach depends on an embedding algorithm that use a clustering method in combination with swarm algorithm to divide the mesh model vertices into groups. A Points of interest set (POIs) are selected from these groups and mark it as watermark carriable vertices. This proposed approach inserts the watermark bitstream in the decimal part of spherical coordinates for these selected vertices. The experimental results confirm that the proposed optimization approach of watermark position Abstract selection and embedding proves its superiority compared with other techniques with respect to imperceptibility and robustness. On the other hand, we proposed another Intelligent approach that embedding the watermark bitstream using the Coyote optimization algorithm. The approach starts by selecting the best vertices that will carry the watermark bits using k-means clustering method. Followed by watermark embedding step using COA in finding the best local statistical measure modification value. Finally, we extract the embedded watermark without any need of the original model. The proposed approach is validated using different visual fidelity and robustness measures. The experimental results of the proposed approach will be compared with other state of the art approaches to prove its superiority in embedding and extraction of watermark bits sequence with respect to both robustness and impracticability. Keywords: Three-dimensions model, Watermark, Machine learning, Particle Swarm optimization, Coyote optimization algorithm, Spherical coordinates, Statistical distribution. |