MURAL - Maynooth University Research Archive Library



    A Comparative Study of Chaotic and White Noise Signals in Digital Watermarking


    Mooney, Aidan and Keating, John and Pittas, Ioannis (2008) A Comparative Study of Chaotic and White Noise Signals in Digital Watermarking. Chaos, Solitions and Fractals, 35 (5). pp. 913-921. ISSN 0960-0779

    [img] Download (237kB)


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    Digital Watermarking is an ever increasing and important discipline, especially in the modern electronically-driven world. Watermarking aims to embed a piece of information into digital documents which their owner can use to prove that the document is theirs, at a later stage. In this paper, performance analysis of watermarking schemes is performed on white noise sequences and chaotic sequences for the purpose of watermark generation. Pseudorandom sequences are compared with chaotic sequences generated from chaotic skew tent map. In particular, analysis is performed on highpass signals generated from both these watermark generation schemes, along with analysis on lowpass watermarks and white noise watermarks. This analysis focuses on the watermarked images after they have been subjected to common image distortion attacks. It is shown that signals generated from highpass chaotic signals have superior performance than highpass noise signals, in the presence of such attacks. It is also shown that watermarks generated from lowpass chaotic signals have superior performance over the other signal types analysed.

    Item Type: Article
    Additional Information: Preprint version of original published article.
    Keywords: White Noise Signals; Digital Watermarking;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 743
    Depositing User: Aidan Mooney
    Date Deposited: 17 Oct 2007
    Journal or Publication Title: Chaos, Solitions and Fractals
    Publisher: Elsevier Science
    Refereed: Yes
    URI:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year