Sliding Window used for Robustness and Fidelity Optimization Employing Neighborhood Concept and Genetic Algorithm with Tournament Selection
|
10.5120/2452-3310 |
Sachin Goyal and Roopam Gupta. Article: Sliding Window used for Robustness and Fidelity Optimization Employing Neighborhood Concept and Genetic Algorithm with Tournament Selection. International Journal of Computer Applications 20(8):36-42, April 2011. Full text available. BibTeX
@article{key:article,
author = {Sachin Goyal and Roopam Gupta},
title = {Article: Sliding Window used for Robustness and Fidelity Optimization Employing Neighborhood Concept and Genetic Algorithm with Tournament Selection},
journal = {International Journal of Computer Applications},
year = {2011},
volume = {20},
number = {8},
pages = {36-42},
month = {April},
note = {Full text available}
}
Abstract
Digital media security is the principal concern in the today’s technological world. Due to easy production, transmission and dissemination of digital data, security threats occur while dealing with digital data. Digital watermarking is one of the growing and promising technologies to protect the digital data from being tampered and also widely used for copyright protection. Several watermarking techniques in spatial and frequency domain were given by various researchers which suffered from problems of poor robustness and fidelity. The evolutionary techniques using genetic algorithm provide an alternative way of creating watermarks with promising values of robustness and fidelity aspect of watermarking. This paper deals with design and development of a new watermarking technique which uses genetic algorithm to identify locations within the cover image for watermark insertion in spatial domain and then apply the average neighborhood concept for the purpose of watermark insertion and extraction ensuring higher fidelity and robustness and resilience to several possible image attacks. Genetic search often produces same watermark locations in different populations for watermark insertion resulting in poor value of fidelity and robustness, which need to be checked. Sliding window concept introduced in this paper uses a set of a few genes which are serially shuffled to get new set of locations for watermarking during each population generation and helps in enhancing robustness and fidelity aspect of watermarking. Tournament selection has been used while using the genetic algorithms developed in the paper.
Reference
- SachinGoyal, R.Gupta, A.Bansal “ Survey of Digital Watermarking with Genetic Algorithm” in Computer Society of India Communication Jan-2010.pp22-25.
- R.G.Van Schyndel,A.Z.Tirkel and CF.Osborene, “A Digital Watermark” in Proc. IEEE International Conf. Image processing,1994,vol.2 pp 86-92.
- J.Cox,J.Kilian , “A Secure Robust Watermark for Multimedia” in Proc. First International Workshop, vol 1174 of Lecture notes in computer science, pp. 185-206.
- Yen, Shwu Huey, et al. “ A Watermarking Technique based on JPEG quantization table.” Taipei, Taiwan: Proceeding of the 2006 International Computer Symposium (ICS2006).
- B.Sikander, M. Iahiaq, M.A. Jaffer,M.Tariq, A. Mirza “Adaptive digital watermarking of images using Genetic Algorithm” in Proc IEEE.
- Huang ,Pan, Shieh and Wang “Progressive watermarking techniques with genetic Algorithms” IEEE, 2003.
- M.J. Anwar, M.Ishtiaq, M.Iqqbal, M,Jaffar “ Blocked-based digital image watermarking using Genetic Algorithm” in Proc IEEE international conference on Emerging Technologies(ICET) 2010. pp 204-208.
- Somying Promchareon and Yuttapong Rangsanseri. “ Genetic watermarking with Block-Based DCT Clustering in IEEE International Symposium on Communication and Information Technologies(ISCIT-2008). Pp 346-351
- M.rafigh and M.Ebrahimi “ A Robust Evolutionary Based Digital Image Watermarking Technique in DCT Domain” in Proc IEEE Seventh International Conference on Computer Graphics, Imaging and Visualization 2010.pp 105-109.
- Sachin Goyal and Roopam Gupta “Optimization of fidelity with Adaptive genetic watermarking algorithm using roulette-wheel” in proc IEEE International conf. On Computational Intelligence Communication Networls”, 2010. pp 591-596.
- Goldberg, D.E, “Genetic Algorithm in Search, Optimization & machine learning”, Addison-Weseley, 1989.
- M.Srinivas and Lalit M.Patnaik, “Genetic Algorithm: A Survey” IEEE,1994.
- I.J. Cox, M.L Miller, J.A Bloom “Digital watermarking” Morgam Caufmann.