Earticle

초록

영어

Fast distribution of digital contents through open networks is not posing a significant problem due to digital media revolution. Modern technologies have also reduced the reproduction time of digital media and its fast distribution. However, this facility has also the darker side where unauthorized users can tamper its contents and manipulate the digital data thus giving rise to serious security concerns. This problem has to be addressed very seriously. Digital watermarking techniques have recently evolved to address the above problems. The usage of these digital watermarks prevent illegal reproduction and usage of digital data as well as help in identifying the origin, author, owner etc even after various manipulations or attack on the digital data. A number of watermarking techniques in spatial and frequency domain were given by various researchers which suffered from problems robustness. Genetic algorithm provides an alternative way of creating watermarks with Promising values of robustness 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 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 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 aspect of watermarking. Roulette-wheel selection has been used while using the genetic algorithms developed in the paper.

목차

Abstract
 1. Introduction
 2. Algorithm Optimization of Robustness with Sliding Window Neighborhood Concept Using Genetic Algorithm
 3. Neighborhood Concept
 4. Sliding Window Concept
 5. Experimental Results
 6. Conclusion
 Reference

키워드

저자

• Sachin Goyal [ Department of Information Technology, U.I.T, R.G.P.V, Bhopal ]
• Roopam Gupta [ Department of Information Technology, U.I.T, R.G.P.V, Bhopal ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605