Digital watermarks have been proposed as a method for discouraging illicit copying and distribution of copyrighted material, and to create secure digital image libraries by adding to images copyright and user-right information. Using a robust digital watermark to detect and trace copyright violations has therefore lot of interest. This paper describes an approach to embedding a digital watermark using the Fourier transform. The paper also addresses the difficult problem of oblivious watermark detection. It is shown that, for the CDMA spread spectrum signal described in the paper, it is still possible to positively detect the presence of a watermark without being able to decode it (and even infer the number of bits contained in the watermark) given only the key used to generate it. Finally, through experimental results the usefulness of such measure is shown.

A digital watermark is an invisible mark embedded in a digital image which may be used for copyright protection. This paper proposes that Fourier-Mellin transform-based invariants can be used for digital image watermarking. The embedded marks may be designed to be unaffected by any combination of rotation, scale and translation transformations. The original image is not required for extracting the embedded mark.

A watermark is an invisible mark placed on an image that can be detected when the image is compared with the original. This mark is designed to identify both the source of an image as well as its intended recipient. The mark should be tolerant to reasonable quality lossy compression of the image using transform coding or vector quantization. Standard image processing operations such as low pass filtering, cropping, translation and rescaling should not remove the mark. Spread spectrum communication techniques and matrix transformations can be used together to design watermarks that are robust to tampering and are visually imperceptible. This paper discusses techniques for embedding such marks in grey scale digital images. It also proposes a novel phase based method of conveying the watermark information. In addition, the use of optimal detectors for watermark identification is also proposed.

This paper presents a Bayesian approach to the location of a discontinuity in linearly modelled data. A matrix formulation is introduced which allows the modelling of changepoints in general linear models. Linear models investigated include abrupt changes in the mean of a Gaussian random variable, and piecewise polynomials such as splines, as well as autoregressive models. The approach facilitates the removal of nuisance parameters by integration. A general recursive technique for updating Bayesian posterior densities, which can result in large savings in computation, is also described.>