Skip to main content

Research Repository

Advanced Search

A steganalytic algorithm for 3D polygonal meshes

Yang, Ying; Pintus, Ruggero; Rushmeier, Holly; Ivrissimtzis, Ioannis

A steganalytic algorithm for 3D polygonal meshes Thumbnail


Authors

Ying Yang

Ruggero Pintus

Holly Rushmeier



Abstract

We propose a steganalytic algorithm for watermarks embedded by Cho et al.'s mean-based algorithm [1]. The main observation is that while in a clean model the means of Cho et al.'s normalized histogram bins are expected to follow a Gaussian distribution, in a marked model their distribution will be bimodal. The proposed algorithm estimates the number of bins through an exhaustive search and then the presence of a watermark is decided by a tailor made normality test. We also propose a modification of Cho et al.'s algorithm which is more resistant to the steganalytic attack and offers an improved robustness/capacity trade-off.

Citation

Yang, Y., Pintus, R., Rushmeier, H., & Ivrissimtzis, I. (2014, October). A steganalytic algorithm for 3D polygonal meshes. Presented at 2014 IEEE International Conference on Image Processing (ICIP), Paris, France

Presentation Conference Type Conference Paper (published)
Conference Name 2014 IEEE International Conference on Image Processing (ICIP)
Acceptance Date May 30, 2014
Publication Date Oct 1, 2014
Deposit Date Apr 15, 2016
Publicly Available Date Apr 19, 2016
Pages 4782-4786
Series ISSN 1522-4880
Book Title ICIP 2014 : 2014 IEEE International Conference on Image Processing (ICIP).
DOI https://doi.org/10.1109/icip.2014.7025969
Public URL https://durham-repository.worktribe.com/output/1150533

Files

Accepted Conference Proceeding (294 Kb)
PDF

Copyright Statement
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.






You might also like



Downloadable Citations