Adaptive digital image watermarking based on predictive embedding and a Dynamic Fuzzy Inference System model

  • Authors:
  • Nizar Sakr;Jiying Zhao;Voicu Z. Groza

  • Affiliations:
  • School of Information Technology and Engineering, University of Ottawa, 800 King Edward Ave., Ottawa, ON K1N 6N5, Canada.;School of Information Technology and Engineering, University of Ottawa, 800 King Edward Ave., Ottawa, ON K1N 6N5, Canada.;School of Information Technology and Engineering, University of Ottawa, 800 King Edward Ave., Ottawa, ON K1N 6N5, Canada

  • Venue:
  • International Journal of Advanced Media and Communication
  • Year:
  • 2007

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Abstract

This paper presents a novel robust watermarking technique intended for the application of copyright protection. A dynamic fuzzy inference system is modelled and used in conjunction with a model of the Human Visual System (HVS) to compute the adaptive strength and length of the watermark. The proposed fuzzy logic technique relies on the statistical distributions of the HVS-generated data to accurately approximate the relationship found between all properties of the visual model. In addition, we introduce a predictive watermark embedding algorithm that exploits the average power of the frequency-domain image coefficients to optimise the watermarking process.