Intelligent Image Watermarking using Genetic Programming

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