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WACA: a new blind robust watermarking method based on Arnold Cat map and amplified pseudo-noise strings with weak correlation

  • Seyyed Hossein Soleymani
  • Amir Hossein TaheriniaEmail author
  • Amir Hossein Mohajerzadeh
Article
  • 2 Downloads

Abstract

In this paper, a robust and blind watermarking method is proposed, which is highly resistant to the common image watermarking attacks, such as noises, compression, and image quality enhancement processing. In this method, Arnold Cat map is used as a pre-processing on the host image, which increases the security and imperceptibility of watermark embedding with a strong gain factor. Moreover, two pseudo-noise strings with weak correlation are used as the symbol of each 0 or 1 bit of the watermark. Accordingly, the accuracy increases in detecting the status of watermark bits at extraction phase in comparison to using two random pseudo-noise strings. Moreover, to increase the robustness and further imperceptibility of the embedding, the Arnold Cat mapped image is subjected to non-overlapping block. Then, the high-frequency coefficients of the approximation sub-band of FDCuT transform are used as the embedding location for each block. Comparison of the proposed method with recent robust related works under the same experimental conditions indicates the superiority of the proposed method.

Keywords

Data hiding Watermarking Robustness Curvelet transform Arnold Cat map Weak correlation noises 

Notes

Acknowledgments

We have to express our appreciation to Dr. Bolourian Haghighi for assistance and sharing comments that greatly improved the manuscript.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Seyyed Hossein Soleymani
    • 1
  • Amir Hossein Taherinia
    • 1
    • 2
    Email author
  • Amir Hossein Mohajerzadeh
    • 1
  1. 1.Department of Computer Engineering, Faculty of EngineeringFerdowsi University of MashhadMashhadIran
  2. 2.Machine Vision LaboratoryFerdowsi University of MashhadMashhadIran

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