DocumentCode :
3580618
Title :
Watermarking for 3-D Polygon Mesh Using Mean Curvature Feature
Author :
Garg, Hitendra ; Arora, Gagandeep ; Bhatia, Komal
Author_Institution :
Dept. of CSE, Hindustan Coll. of Sci. & Technol., Mathura, India
fYear :
2014
Firstpage :
903
Lastpage :
908
Abstract :
Copyright protection of 3-D objects are also important for protecting author rights in animation, multimedia, computer aided design (CAD), virtual reality, medical imaging etc. Especially in the grown up market of video-games, there is demand for a watermarking technique for 3-D-objects. In this paper, we propose a robust watermarking algorithm having less perceivable distortion for 3-D polygon mesh objects based on geometrical properties. The selection of vertices for watermark embedding is based on perceivable distortion. The perceivable distortion is defined as the distortion observed by human observers. The selection of vertices for watermark embedding is an important factor for perceivable distortion as watermark embedding in deeper surface has less perceivable distortion in comparison to watermark embedding in flat or peak surfaces. In the proposed algorithm, we exploit this observation for selection of vertices for watermark embedding. The watermark is embedded by repositioning the selected vertices from their original positions.
Keywords :
computer graphics; image watermarking; mesh generation; 3D polygon mesh; CAD; animation; computer aided design; copyright protection; geometrical properties; human observers; mean curvature feature; medical imaging; multimedia; peak surfaces; perceivable distortion; robust watermarking algorithm; video games; virtual reality; watermark embedding; watermarking technique; Algorithm design and analysis; Correlation; Distortion measurement; Measurement uncertainty; Robustness; Smoothing methods; Watermarking; 3-D Polygon Mesh; Hausdorff distance; Mean Curvature; Objective measurement; RMS distance; Subjective measurement; perceivable visual quality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2014 International Conference on
Print_ISBN :
978-1-4799-6928-9
Type :
conf
DOI :
10.1109/CICN.2014.190
Filename :
7065610
Link To Document :
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