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The Maximum Capacity and Minimum Detectable Capacity of Information Hiding in Digital Images

  • Fan Zhang
  • Xianxing Liu
  • Jie Li
  • Xinhong Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3981)

Abstract

Information hiding capacity of digital image is the maximum information that can be hidden in an image. But the lower limit of information hiding, the minimum detectable information capacity is also an interesting problem. This paper proposes new method of the information hiding capacity bounds analysis that is based on the theories of attractors and attraction basin of neural network. The upper limit and lower limit of information hiding, namely the maximum information capacity and the minimum detectable information capacity are unified in a same theory frame. The results of research show that the attraction basin of neural network decides the upper limit of information hiding, and the attractors of neural network decide the lower limit of information hiding.

Keywords

Neural Network Image Watermark Information Hiding Digital Watermark Stego Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fan Zhang
    • 1
  • Xianxing Liu
    • 1
  • Jie Li
    • 1
  • Xinhong Zhang
    • 2
  1. 1.College of Computer & Information EngineeringHenan UniversityKaifengP.R. China
  2. 2.Department of Computer CenterHenan UniversityKaifengP.R. China

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