Vassilios Solachidis

Circularly symmetric watermark embedding in 2-D DFT domain

This paper presents an algorithm for rotation and scale invariant watermarking of digital images. An invisible mark is embedded in magnitude of the DFT domain. It is robust to compression, filtering, cropping, translation and rotation. The watermark introduces image changes that are invisible to the human eye. The detection algorithm does not require the original image.

A benchmarking protocol for watermarking methods

A benchmarking system for watermarking algorithms is described. The proposed benchmarking system can be used to evaluate the performance of watermarking methods used for copyright protection, authentication, fingerprinting, etc. Although the system described is used for image watermarking, the general framework can be used, by introducing a different set of attacks, for benchmarking of video and audio data.

Fourier descriptors watermarking of vector graphics images

A blind method for watermarking of vector graphics images through polygonal line modification is proposed. The watermark is embedded in the Fourier descriptors of the polygonal lines, causing invisible distortions to the vertices coordinates. The properties of the Fourier descriptors ensure that watermarks generated by this technique withstand rotation, translation, scaling, reflection, change of traversal starting point/direction and smoothing.

A survey on watermarking application scenarios and related attacks

A thorough investigation on all possible scenarios where digital imperceptible watermarking is applicable is presented. All previously proposed watermarking schemes fall to at least one of the referenced application categories. Possible attacks are divided into categories and application scenarios are presented, always referring to the watermarking parameters involved.

Performance analysis of correlation-based watermarking schemes employing Markov chaotic sequences

In this paper, theoretical performance analysis of watermarking schemes based on correlation detection is undertaken, leading to a number of important observations on the watermarking system detection performance. Statistical properties of watermark sequences generated by piecewise-linear Markov maps are investigated. Correlation/spectral properties of such sequences are easily controllable, which is a fact that reflects on the watermarking system performance. A family of chaotic maps, namely the skew tent map family, is used to verify the theoretical analysis. Skew tent chaotic sequences are compared against the widely used pseudorandom sequences, indicating the superiority of the former in watermarking applications. The minimum number of samples required for reliable watermark detection is also investigated. Experiments using audio data are conducted to verify the theoretical analysis results.

Watermark detection: benchmarking perspectives

Benchmarking of watermarking algorithms is a complicated task that requires examination of a set of mutually dependent performance factors (algorithm complexity, decoding/detection performance, and perceptual quality). This paper will focus on detection/decoding performance evaluation and try to summarize its basic principles. A methodology for deriving the corresponding performance metrics will also be provided.

Applications of chaotic signal processing techniques to multimedia watermarking

Usage of digital media has witnessed a tremendous growth during the last decades. However digital media are extremely vulnerable to copyright infringement, tampering and unauthorized distribution. Recently the protection of digital information has received significant attention within the digital media community and a number of techniques that try to address the problem by hiding appropriate information within digital media have been proposed. In this paper we present two applications of chaotic systems to watermarking of multimedia data, namely secure spatial scrambling of watermark patterns prior to their embedding in images and generation of 1-D or 2-D watermark signals.

Watermarking polygonal lines using Fourier descriptors

Digital products are easy to copy, reproduce, and maliciously process in a network environment. Over the past decade, watermarking has emerged as an important technology for protecting copyright of multimedia products. We present a method for embedding and detecting watermarks in vector graphics images containing polygonal lines, and present results from simulated attacks. Our proposed algorithm embeds watermarks in polygonal lines describing image contours. These contours are usually described in vector format. Our watermarking method slightly modifies the vertex coordinates of the polygonal line. We embed the watermark in the magnitude of the curves Fourier descriptors to exploit its location, scale, and rotation invariant properties. Our technique has certain similarities to bitmap image watermarking in the discrete Fourier transform (DFT) domain. However, its essentially different because it can be applied to vector rather than bitmap images. Furthermore, Fourier descriptor watermarking problems differ from DFT bitmap image watermarking problems.A method for watermarking of polygonal lines is proposed. The watermark is embedded in the Fourier descriptors of the polygonal line causing minor distortions to the coordinates of the vertices of the polygonal line. Watermarks generated by this technique can be successfully detected even after rotation, translation, scaling and reflection of the host polygonal line.

A mutual information based face clustering algorithm for movie content analysis

This paper investigates facial image clustering, primarily for movie video content analysis with respect to actor appearance. Our aim is to use novel formulation of the mutual information as a facial image similarity criterion and, by using spectral graph analysis, to cluster a similarity matrix containing the mutual information of facial images. To this end, we use the HSV color space of a facial image (more precisely, only the hue and saturation channels) in order to calculate the mutual information similarity matrix of a set of facial images. We make full use of the similarity matrix symmetries, so as to lower the computational complexity of the new mutual information calculation. We assign each row of this matrix as feature vector describing a facial image for producing a global similarity criterion for face clustering. In order to test our proposed method, we conducted two sets of experiments that have produced clustering accuracy of more than 80%. We also compared our algorithm with other clustering approaches, such as the k-means and fuzzy c-means (FCM) algorithms. Finally, in order to provide a baseline comparison for our approach, we compared the proposed global similarity measure with another one recently reported in the literature.

Statistical analysis of a watermarking system based on Bernoulli chaotic sequences

The paper deals with the statistical analysis of the behaviour of a blind copyright protection watermarking system based on chaotic watermark signals generated by n-way Bernoulli shift maps. The analysis involves theoretical evaluation of the system detection reliability, when a correlator detector is used. The effect of distortions (lowpass filtering, noise corruption of the watermarked data) on the detection reliability is also theoretically investigated. The system is modelled in a communication framework considering the signal as interference and converting the addressed problem to the detection of the underlying watermark signal. The aim of the paper is two-fold: (i) to introduce the n-way Bernoulli shift generated chaotic watermarks and theoretically contemplate their properties with respect to the detection reliability and (ii) to theoretically establish their potential superiority against the widely used (pseudo-)random watermarks. An important property of Bernoulli watermarks is their controllable spectral/correlation properties that renders them ideal for a variety of applications. Bernoulli watermarks can be generated with lowpass spectral properties to withstand lowpass attacks. When no distortions are to be inflicted, white spectrum Bernoulli watermarks can be generated so that their performance converges to that of the random watermarks. Experimental verification of the theoretical analysis results has been performed as well.