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A Fuzzy Watermarking Approach Based on Human Visual System
Oueslati Sameh, Adnane Cherif, Basel Solaiman
Pages - 218 - 231     |    Revised - 30-06-2010     |    Published - 10-08-2010
Volume - 4   Issue - 3    |    Publication Date - July 2010  Table of Contents
Digital watermarking, Fuzzy inference system, insertion force, The human visual system, Robustness
The implementation of our watermarking system is based on a hybrid system combining the human visual system (HVS) and the fuzzy inference system (FIS), which always passes through the transcription of human expertise in the form of fuzzy rules expressed in natural language, which allows our watermarking system remain understandable for non expert and become more friendly. The technique discussed in this paper is the use of an advanced approach to the technique of watermark that is the multi-watermark or the watermarking multiple of medical images in the frequency domain. In this approach, the emphasis will be on the safe side and the invisibility while maintaining robustness against a certain target range of attacks. Furthermore, this approach is based on an entirely blind technique which we will detail later.
1 Google Scholar 
2 CiteSeerX 
3 iSEEK 
4 Socol@r  
5 Bielefeld Academic Search Engine (BASE) 
6 Scribd 
7 WorldCat 
8 SlideShare 
10 PdfSR 
A. Westfeld. “A Regression-Based Restoration Technique for Automated Watermark Removal”. Multimedia & Security ACM Workshop MMSEC, Oxford, United Kingdom 2008
A. Zaid. “Compression et tatouage d’images à des fins d’archivage et de transmission : application aux images médicale”. Habilitation University El Manar, Tunisia, April 2009
A.B. Watson, “DCT: A technique for visual optimization of DCT quantization matrices for individual images”. Society for Information Display Digest of Technical Papers, pp. 946-949, 1993
B. Mathon, P. Bas, F. Cayre. “Practical performance analysis of secure modulations for WOA spread-spectrum based image watermarking”. Multimedia and Security Workshop, Dallas, Texas, USA, 2007
B. Miladi, M. Sayadi and F. Fnaiech. “Textures synthesis methods”. International Conference on Electrical Systems and Automatic control, Tunisia, 2010
C. REY. “Tatouage d’image: Gain en robustesse et intégrité des images”. PhD Thesis, University of Avignon and Pays de Vaucluse, 2003
Coatrieux G.,Puentes J.,Lecornu L., Roux. C., “Compliant secured specialized electronic patient record platform”. In D2H2'00, Proceedings of D2H2, Washington, Etats-Unis, 2006
F.Davoine and S.Pateux. “Tatouage de documents audiovisuels numériques”. Livre édition Hermès Lavoisier, traité IC2 Série Traitement du signal et de l’image, (2004).
G. Coatrieux M. Lamard, W.J. Puente, and C. Roux “A low distortion and reversible watermark: Application to angiographic images of the retina”. In EMBC'05, Proceedings of Int. Conference of the IEEE-EMBS, p. 2224-2227, Shangaï, Chine, 2005
G. Coatrieux, H. Maitre. “Images médicales, sécurité et tatouage”. Annales des Télécommunications, Numéro Spécial Santé, vol. 58, p. 782-800, 2003
J.Reichel and M.Kunt. “Performance comparison of masking models based on a new psychovisual test method with natural scenery stimuli”. Signal processing: Image communication, 17:807-823, 2002
J.Zhao, E.Koch. “Towards robust and hidden image copyright labelling”. IEEE Workshop on Nonlinear Signal and Image Processing, 1995
L. Lin, I. J. Cox and G. Doerr. “An efficient algorithm for informed embedding of dirty-paper trellis codes for watermarking”. IEEE Int. Conference on Image Processing, 2005
M. Barni, F. Bartolini, V. Cappellini and A. Piva, “A DCT domain system for robust image watermarking”. Signal Processing, vol. 66, no. 3, pp. 357-372, 1998
M. Vincent. “Contribution des filtres LPTV et des techniques d’interpolation au tatouage numérique”. PhD Thesis presented in Toulouse, 2006
M.Kutter and S.Winkler. “A Vision-based Masking Model for Spread-Spectrum Image Watermarking”. IEEE Transactions on Image processing, 1(2): 244-250, 2002
N. Palluat. ”Méthodologie de surveillance dynamique à l'aide des réseaux neuro-fous temporels”. PhD Thesis, University of Franche-Comte, 2006
N.S. Jayant, J.D. Johnson and R. Safranek. “Signal compression based on models of human perception”. Proceedings of IEEE, Volume 81, No. 10, pp. 1385-1422, 1993
N.sakr et al. “Copyright protection of learning using wavelet objects using wavelet-based watermarking and fuzzy logic, 3rd annual e-learning conference on Intelligent Interactive learning Object”. Repositories Montreal. Quebec, Canada, 2006
O. Cadet. ”Méthodes d'ondelettes pour la segmentation d'images : Applications à l'imagerie médicale et au tatouage d'images”. PhD Thesis at the Polytechnic Institute of Grenoble, 2004
P. Bas, F. Cayre, B. Mathon. “Techniques sures de tatouage pour l’image”. Compression et Représentation des Signaux Audiovisuels, Montpellier, France, 2007
Patrick Bas and François Cayre, Natural Watermarking: a secure spread spectrum technique for WOA Information Hiding”, pp.1-14, 4437, 2006
S. Geetha, Siva S. Sivatha Sindhu, N. Kamaraj. “Close Color Pair Signature Ensemble Adaptive Threshold based Steganalysis for LSB Embedding in Digital Images”. Transactions on Data Privacy, pp. 140 – 161, 2008
S. Pereira. “Robust Digital Image Watermarking”. PhD Thesis, University of Geneva, 2000
S. Zaboli, A. Tabibiazar and R. Safabakhsh. “Entropy-Based image watermarking using DWT and HVS”. 3rd International Conference of Sciences of Electronic, Technologies of Information and Telecommunications, Tunisia, 2005
Miss Oueslati Sameh
University of Sciences of Tunis - Tunisia
Mr. Adnane Cherif
- Tunisia
Mr. Basel Solaiman
- France