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.
|Full text:||(AM) Accepted Manuscript|
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|Publisher Web site:||http://dx.doi.org/10.1145/2535555|
|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) http://doi.acm.org/10.1145/2535555|
|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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