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Mesh Discriminative Features for 3D Steganalysis

Yang, Ying; Ivrissimtzis, Ioannis

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Authors

Ying Yang



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 29, 2024
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

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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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