Ying Yang
Mesh Discriminative Features for 3D Steganalysis
Yang, Ying; Ivrissimtzis, Ioannis
Abstract
We propose a steganalytic algorithm for triangle meshes, based on the supervised training of a classifier by discriminative feature vectors. After a normalization step, the triangle mesh is calibrated by one step of Laplacian smoothing and then a feature vector is computed, encoding geometric information corresponding to vertices, edges and faces. For a given steganographic or watermarking algorithm, we create a training set containing unmarked meshes and meshes marked by that algorithm, and train a classifier using Quadratic Discriminant Analysis. The performance of the proposed method was evaluated on six well-known watermarking/steganographic schemes with satisfactory accuracy rates.
Citation
Yang, Y., & Ivrissimtzis, I. (2014). Mesh Discriminative Features for 3D Steganalysis. ACM Transactions on Multimedia Computing, Communications and Applications, 10(3), Article 27. https://doi.org/10.1145/2535555
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 25, 2013 |
Online Publication Date | Apr 17, 2014 |
Publication Date | Apr 17, 2014 |
Deposit Date | Feb 24, 2016 |
Publicly Available Date | Mar 1, 2016 |
Journal | ACM Transactions on Multimedia Computing, Communications and Applications |
Print ISSN | 1551-6857 |
Electronic ISSN | 1551-6865 |
Publisher | Association for Computing Machinery (ACM) |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Issue | 3 |
Article Number | 27 |
DOI | https://doi.org/10.1145/2535555 |
Public URL | https://durham-repository.worktribe.com/output/1390781 |
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Copyright Statement
© 2014 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Multimedia Computing, Communications and Applications, 10, 3, Article No.27 (April 2014) http://doi.acm.org/10.1145/2535555
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