Open AccessStatistical watermarking approach for 3D mesh using local curvature estimation
Author(s) -
Sharma Neha,
Panda Jeebananda
Publication year - 2020
Publication title -
iet information security
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 34
eISSN - 1751-8717
pISSN - 1751-8709
DOI - 10.1049/iet-ifs.2019.0601
Subject(s) - watermark , digital watermarking , robustness (evolution) , vertex (graph theory) , curvature , neighbourhood (mathematics) , polygon mesh , mathematics , triangle mesh , algorithm , computer science , artificial intelligence , pattern recognition (psychology) , theoretical computer science , geometry , image (mathematics) , mathematical analysis , graph , biochemistry , chemistry , gene
In this study, an oblivious 3D mesh watermarking scheme is represented utilising local curvature estimation and statistical characteristics of 3D mesh to provide robustness as well as retaining the imperceptibility of the 3D model. The proposed method estimates the local curvature of 3D model by finding the difference between the average normal and the surface normal of all the faces in a 1‐ring neighbourhood of a vertex under consideration. Feature vector of all vertices is then measured and used to select vertices for watermark insertion. Distributions of vertex norms are transformed statistically to hide the watermark as statistical parameters are more robust and less prone to attacks. The robustness and imperceptibility of the proposed method against various attacks are analysed through simulations.