Paper Info
Title
3D multimedia protection using artificial neural network
Abstract
Watermarking based DRM implementations insert imperceptible information or watermark in digital media to trace owner of the content and deter the illegal distribution of media. In geometry based 3D watermarking algorithms, a watermark is inserted by modifying the coordinates of vertices in the mesh. It is a requirement of watermarking algorithms that this change in vertex coordinates shouldn't cause perceptible distortion. It has always been a challenge to select vertices in the 3D model which would not cause perceptible distortion on addition of watermark. This paper proposes a novel approach to overcome this challenge using Artificial Neural Networks (ANN). Feature vectors representing the geometry of the vertex and its surrounding vertices are extracted and used to train and simulate ANN. ANN is used as a classifier to determine which vertices should be selected for watermarking. Experimental results simulate various attacks to test the robustness of the algorithm.
Year
DOI
Venue
2010
10.1109/CCNC.2010.5421700
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
Keywords
Field
DocType
watermarking algorithm,novel approach,surrounding vertex,perceptible distortion,artificial neural networks,illegal distribution,multimedia protection,various attack,digital media,drm implementations insert imperceptible,artificial neural network,feature vector,3d,back propagation,indexing terms,vectors,digital rights management,watermarking,neural nets
Digital watermarking,Feature vector,Vertex (geometry),Computer science,Computer network,Robustness (computer science),Watermark,Artificial neural network,Backpropagation,Distortion
Conference
ISSN
ISBN
Citations 
2331-9852
978-1-4244-5176-0
1
PageRank 
References 
Authors
0.37
5
5
Name
Order
Citations
PageRank
Mukesh C. Motwani1164.60
Bobby D. Bryant2586.70
Sergiu Dascalu336279.10
Frederick C. Harris Jr.454778.86
Harris, F.C.510.37