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Mesh discriminative features for 3D steganalysis.

Yang, Ying and Ivrissimtzis, Ioannis (2014) 'Mesh discriminative features for 3D steganalysis.', ACM transactions on multimedia computing, communications and applications., 10 (3). p. 27.


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.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Publisher 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)
Date accepted:25 September 2013
Date deposited:01 March 2016
Date of first online publication:17 April 2014
Date first made open access:01 March 2016

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