An optimal image watermarking approach based on a multi-objective genetic algorithm

  • Authors:

  • Jun Wang;Hong Peng;Peng Shi

  • Affiliations:

  • School of Electrical and Information Engineering, Xihua University, Chengdu, Sichuan 610039, China;School of Mathematics and Computer Engineering, Xihua University, Chengdu, Sichuan 610039, China;Department of Computing and Mathematical Sciences, University of Glamorgan Pontypridd, CF37 1DL, UK and School of Engineering and Science, Victoria University Melbourne, Vic 8001, Australia

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2011

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Abstract

In accordance with the multi-objective nature of image watermarking, an optimal image watermarking approach using a multi-objective genetic algorithm is presented in this paper. Both watermarking parameters and embedding positions are often important factors affecting the performance of watermarking systems. The proposed multi-objective watermarking method can automatically optimize system parameters, and a variable-length mechanism is specially designed to search the most suitable positions for embedding watermarks. The method can also remove the difficult issue of determining optimal watermarking parameters from previous watermarking algorithms. The proposed multi-objective watermarking method directly deals with the problem of optimizing watermarking under non-dominated meaning, thus it can effectively avoid the difficulty of determining the optimally weighted factor in existing single-objective watermarking schemes. In addition, a Pareto-optimal set generated by multi-objective optimization can provide flexibility in selecting the most suitable watermarking parameters according to practical requirements.