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Durham University

Research & business

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Publication details for Dr Ioannis Ivrissimtzis

Yang, Ying & Ivrissimtzis, Ioannis (2014). Mesh Discriminative Features for 3D Steganalysis. ACM Transactions on Multimedia Computing, Communications, and Applications 10(3): 27.

Author(s) from Durham


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.