• DocumentCode
    3484281
  • Title

    Decision of image watermarking strength based on artificial neural-networks

  • Author

    Shi-Chun, Mei ; Ren-Hou, Li ; Hong-Mei, Dang ; Yun-Kuan, Wang

  • Author_Institution
    Syst. Eng. Inst., Xi´´an Jiaotong Univ., China
  • Volume
    5
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    2430
  • Abstract
    Digital watermarking is a new technique for digital multimedia copyright protection. The robustness and the imperceptibility are the basic requirements of the digital watermark. The key factor that affects both the robustness and the imperceptibility of the digital watermark is the watermarking strength. In this paper, artificial neural network (ANN) is used to model human visual system (HVS) and an ANN-based image-adaptive method for deciding watermarking strength for image DCT coefficients is presented. The experimental results show that the method can increase the watermarking strength so that the robustness of digital watermark is enhanced and that the method has very good adaptability.
  • Keywords
    binary sequences; discrete cosine transforms; feedforward neural nets; image coding; iterative methods; learning (artificial intelligence); transform coding; watermarking; DCT coefficients; Levenberg-Marquardt algorithm; Sigmoid function; artificial neural network; digital multimedia copyright protection; digital watermarking; feedforward neural network; human visual system; image watermarking strength decision; image-adaptive method; imperceptibility; pseudo random binary sequence; robustness; Artificial neural networks; Copyright protection; Discrete cosine transforms; Frequency; Humans; Image coding; Robustness; Systems engineering and theory; Visual system; Watermarking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1201930
  • Filename
    1201930