Earticle

초록

영어

In this paper, we propose a fragile watermarking hybrid approach using rough set kmeans
and exponential particle swarm optimization (EPSO) systems. It is based on a
block-wise dependency mechanism which can detect any alterations made to the protected
image. Initially, the input image is divided into blocks with equal size in order to improve
image tamper localization precision. Then feature sequence is generated by applying rough
k-means and EPSO clustering to create the relationship between all image blocks and cluster
all of them since EPSO is used to optimize the parameters of rough k-means. Both feature
sequence and generated secret key are used to construct the authentication data. Each
resultant 8-bit authentication data is embedded into the eight least significant bits (LSBs)
of the corresponding image block. We gives experimental results which show the feasibility
of using these optimization algorithms for the fragile watermarking and demonstrate the
accuracy of the proposed approach. The performance comparison of the approach was also
realized. The performance of a fragile watermarking approach has been improved in this
paper by using exponential particle swarm optimization (EPSO) to optimize the rough kmean
parameters. The proposed approach can embed watermark without causing noticeable
visual artifacts, and does not only achieve superior tamper detection in images accurately,
it also recovers tampered regions effectively. In addition, the results show that the proposed
approach can effectively thwart different attacks, such as the cut-and paste attack and collage
attack, while sustaining superior tamper detection and localization accuracy.

목차

Abstract
 1 Introduction
 2 Preliminaries: Rough Sets and Particle Swarm Optimization
  2.1 Rough sets
  2.2 Particle swarm optimization
 3 Some improvement
  3.1 Adaptation of K-means to rough set theory
  3.2 Exponential particle swarm optimization
 4 A Block wise-based fragile watermarking approach
  4.1 Rough K-means and exponential particle swarm algorithm
  4.2 Watermark embedding procedure
  4.3 Tamper detection phase
 5 Experimental results and analysis
  5.1 Performance evaluation
  5.2 Performance comparisons and analysis
 6 Conclusions
 References

키워드

저자

• Lamiaa M. El Bakrawy [ Al-Azhar University, Faculty of Science, Cairo, Egypt ]
• Neveen I. Ghali [ Al-Azhar University, Faculty of Science, Cairo, Egypt ]
• Tai-hoon Kim [ Hannam University, Korea ]
• Aboul ella Hassanien [ Cairo University, Faculty of Computers and Information, Cairo, Egypt ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605