• DocumentCode
    2660142
  • Title

    Hybrid Multiplicative Watermarking and Its Decoders

  • Author

    Wang, Jinwei ; Lian, Shiguo ; Yan, Leiming ; Wang, Yuxiang

  • Author_Institution
    Jiangsu Eng. Center of Network Monitoring, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • fYear
    2011
  • fDate
    4-6 Nov. 2011
  • Firstpage
    618
  • Lastpage
    622
  • Abstract
    With the rapid development and the richer content of the Internet, the copyright protection of the works should be further developed. The watermarking has become a possible solution. In this paper, firstly, a novel hybrid multiplicative rule is presented and utilized to embed the watermark into DWT coefficients controlled by the secret key. Secondly, the optimum and locally optimum hybrid multiplicative multi-watermarking decoders are proposed, respectively, which are based on the minimum Bayesian risk criterion. The DWT coefficients are modeled as the generalized Gaussian distribution. Nextly, the performance of the optimum hybrid watermarking decoder, i.e. the average bit error rate is theoretically analyzed. Then the security of the hybrid multiplicative watermarking scheme is compared with the existing schemes. Finally, experimental results prove the theoretical analysis valid.
  • Keywords
    Gaussian distribution; Internet; belief networks; watermarking; wavelet transforms; Bayesian risk criterion; DWT coefficients; Internet; generalized Gaussian distribution; hybrid multiplicative watermarking; multiwatermarking decoders; secret key; Bit error rate; Decoding; Discrete wavelet transforms; Gaussian distribution; Robustness; Watermarking; hybrid decoder; hybrid embedding rule; optimum and lcoally optimum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Information Networking and Security (MINES), 2011 Third International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4577-1795-6
  • Type

    conf

  • DOI
    10.1109/MINES.2011.106
  • Filename
    6103848