• DocumentCode
    3231747
  • Title

    A Robust 3D Model Watermarking Scheme Based on Feature Recognition

  • Author

    Yang, Shu-Guo ; Li, Chun-Xia ; Sun, Sheng-he ; Xu, Yao-Qun

  • Author_Institution
    Qingdao Univ. of Sci. & Technol., Qingdao
  • Volume
    3
  • fYear
    2007
  • fDate
    July 30 2007-Aug. 1 2007
  • Firstpage
    989
  • Lastpage
    993
  • Abstract
    Copyright protection becomes a more and more important problem with the development of the creation and distribution of 3D model. The paper proposes a novel and robust watermarking scheme for 3D model based on the feature recognition method. Firstly, we construct the Cartesian coordinates in 3D model and extract six 2D images from six different directions according to the habit of human recognition. Secondly, We divide the images into 8times8 blocks and transform them in DCT domain, then embed the watermark into the middle-frequency coefficients according to the JND model of the human visual system. Finally, we retrieve the 3D model which is embedded the watermark into. The watermarking detection process is averse to the watermarking embedding process. Many experimental results show that this watermarking scheme is imperceptible, robust and able to withstand common attacks on 3D models such as mesh simplification, adding noise, model cropping.
  • Keywords
    copy protection; copyright; discrete cosine transforms; image recognition; watermarking; Cartesian coordinates; copyright protection; feature recognition; human recognition; human visual system; robust 3D model watermarking scheme; Artificial intelligence; Copyright protection; Discrete cosine transforms; Distributed computing; Humans; Noise robustness; Software engineering; Sun; Visual system; Watermarking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-0-7695-2909-7
  • Type

    conf

  • DOI
    10.1109/SNPD.2007.274
  • Filename
    4287993