Intelligent Image Watermarking using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@PhdThesis{Jan:thesis,
  author =       "Zahoor Jan",
  title =        "Intelligent Image Watermarking using Genetic
                 Programming",
  school =       "Department Of Computer Science, National University Of
                 Computer and Emerging Sciences, Islamabad",
  year =         "2011",
  address =      "Pakistan",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://eprints.hec.gov.pk/7540/1/1016S.htm",
  URL =          "http://prr.hec.gov.pk/Thesis/1016S.pdf",
  size =         "128 pages",
  abstract =     "Multimedia applications are becoming increasingly
                 significant in modern world.The mushroom growth of
                 multimedia data of these applications, particularly
                 over the web has increased the demand for protection of
                 copyright.Digital watermarking is much more acceptable
                 as a solution to the problem of copyright protection
                 and authentication of multimedia data while working in
                 a networked environment.In this thesis a DWT based
                 watermarking scheme is proposed. Wavelet transform is
                 used because it has a number of advantages over other
                 transforms, such as DCT.

                 It has multi-resolution hierarchical characteristics,
                 and lower resolution embedding and detection which are
                 computationally inexpensive.

                 The presentation of the image because of the
                 hierarchical multi-resolution properties of the
                 transformation is well-suited for applications where
                 the multimedia data is transmitted regularly, as such
                 in the application of video systems, or applications in
                 real time.

                 Wavelet transform is closer to HVS contrast to DCT. For
                 this reason, the range of artifacts introduced by
                 wavelet is less infuriating as compared to DCT.

                 For better imperceptibility, the watermarking technique
                 should support a vision model which integrates various
                 masking effects of the Human Visual System (HVS), to
                 embed watermark in an invisible manner. For HVS we have
                 used Watson's Perceptual Model of JPEG2000. The basic
                 aim of perceptual coding is, to conceal the watermark
                 below the detection threshold.This can be obtained by
                 making use of the HVS and JND threshold.The
                 watermarking technique based on this model resists all
                 types of common signal processing operations and many
                 geometric attacks but unfortunately was not resistant
                 against rotation.

                 Keeping in mind this we explored Morton scanning.
                 Morton scanning is used to frequency wise arrange the
                 coefficients to resist geometric attacks. We have used
                 Genetic Programming (GP) in order to make an optimum
                 trade off between imperceptibility and robustness by
                 choosing an optimum watermarking level for each
                 coefficient of the cover image. In addition to the
                 suitable watermarking strength, the selection of best
                 block size is also necessary for superior perceptual
                 shaping functions.To achieve this goal we have trained
                 and used GP to pick the best block size to tailor the
                 watermark in a manner such that it can survive all
                 kinds of intentional and unintentional
                 attacks.Extensive experiments have been carried out, to
                 demonstrate the strong robustness and imperceptibility
                 of the proposed technique over the existing
                 approaches.",
  notes =        "Supervisor: Anwar Majid Mirza",
}

Genetic Programming entries for Zahoor Jan

Citations