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A Survey of Digital Image Watermarking Optimization based on Nature Inspired Algorithms NIAs

초록

영어

Nature-inspired algorithms (NIAs) have gained a significant popularity in recent years to tackle hard real world problems and solve complex optimization functions whose actual solution does not exist. Many new algorithms have been developed which show their capabilities almost in every aspect, where rapid solutions are needed. A survey of the NIAs that are used to find the optimal digital image watermarking has been presented in this paper. Different paradigms have been considered, Genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), ant colony optimization (ACO), bee algorithm (BA), cat swarm optimization (CSO), firefly algorithm (FA) and cuckoo search algorithm (CS) that help to find the optimal digital image watermarking.

목차

Abstract
 1. Introduction
 2. Nature Inspired Algorithms (NIAs) for Optimal Watermarking
  2.1. Genetic Algorithm (GA)
  2.2. Particle Swarm Optimization (PSO)
  2.3. Differential Evolution (DE)
  2.4. Ant Colony Optimization (ACO)
  2.5. Bee Algorithms (BA)
  2.6. Cat swarm Optimization (CSO)
  2.7. Firefly Algorithm (FA)
  2.8. Cuckoo Search Algorithm (CS)
 3. Performance Analysis of Digital Image Watermarking Optimization
 4. Conclusions
 Acknowledgements
 References

저자정보

  • Jumana Waleed School of Information Science and Engineering, Central South University, Changsha, 410083, China, College of Science, University of Diyala, Iraq
  • Huang Dong Jun School of Information Science and Engineering, Central South University, Changsha, 410083, China
  • Thekra Abbas College of Science, Almustanseriah University, Baghdad, Iraq
  • Saad Hameed College of Information Science and Engineering, Hunan University, Changsha, China
  • Hiyam Hatem School of Information Science and Engineering, Central South University, Changsha, 410083, China

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