By Ali Mohammad Al-Haj
In recent times, the large development of electronic expertise has elevated the benefit with which electronic multimedia records are kept, transmitted, and reproduced. simply because conventional copyright tools are mistaken for setting up possession, electronic watermarking is taken into account the most effective strategies to avoid unlawful and malicious copying and distribution of electronic media. complex suggestions in Multimedia Watermarking: photograph, Video and Audio functions introduces readers to cutting-edge examine in multimedia watermarking. masking new developments in electronic photo watermarking and strategies for implementation and optimization throughout diverse media, this ebook is a necessary significant other for pros and researchers operating in components resembling rfile watermarking, multimedia fingerprinting, info hiding, secured e-commerce, copyright safety, and implementation of real-time multimedia watermarking.
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Extra resources for Advanced Techniques in Multimedia Watermarking: Image, Video and Audio Applications
REFERENCES Castleman, K. (1996). Digital Image Processing. Upper Saddle River, NJ: Prentice-Hall. Chan, C. , & Cheng, L. (2004). Hiding data in images by simple LSB substitution. Pattern Recognition, 37, 469–474. , & Wornell, G. (2001). Quantization index modulation: a class of provably good methods for digital watermarking and information embedding. IEEE Transactions on Information Theory, 47(4), 1423–1443. , & Bailey, K. (2003). An evaluation of image based steganography methods. International Journal of Digital Evidence, 2(2), 1–40.
The vertices represent the voxels and the edges represent neighborhood between voxels. The algorithm for this operation is as follows: PROCEDURE construct_graph_from_ keyslice (Slice K, edge); BEGIN for i=0.. width/edge – 3*edge for j=0.. height/3 if i modulo 3=0 then if j modulo 2=0 then K[i] [j]=K[edge*i][edge*j+edge-1]; end if; if j modulo 2 =1 then K[i] [j]=K[edge*i][edge*j+edge+2]; end if; end if; if i modulo 3=1 then if j modulo 2 =0 then K[i] [j]=K[edge*i-1][edge*j-edge]; end if; if j modulo 2 =1 then K[i] [j]=K[edge*i-1][edge*j+edge*2]; end if; end if; if i modulo 3 =2 then if j modulo 2 =0 then K[i] [j]=K[edge*i-2][edge*j+edge-1]; end if; if j modulo 2 =1 then K[i] [j]=K[edge*i-2][edge*j+edge+2]; end if; end if; end for j; end for i; *output the graph END Proposition 3 The total running time of a call of the procedure construct_graph_from_keyslice(Slice K, edge)is O(m*n), where “m” is the width and “n” is the height of image.
For that, a series of significant slices are extracted from the represented 3D model. First, the slicing plane “p” is selected. In order to select the slicing planes a virtual spatial network is used. This network is formed of a set of elementary 3D objects (cells with 12 - cube, 20, 36 or more edges). Each of these cells is formed starting from a basic 2D shape (square, hexagon, octagon) on which is created the corresponding 3D primitives. The faces of these primitives determine the slicing planes.