Sofia Tsekeridou

MPEG-2 error concealment based on block-matching principles

The MPEG-2 compression algorithm is very sensitive to channel disturbances due to the use of variable-length coding. A single bit error during transmission leads to noticeable degradation of the decoded sequence quality, in that part or an entire slice information is lost until the next resynchronization point is reached. Error concealment (EC) methods, implemented at the decoder side, present one way of dealing with this problem. An error-concealment scheme that is based on block-matching principles and spatio-temporal video redundancy is presented in this paper. Spatial information (for the first frame of the sequence or the next scene) or temporal information (for the other frames) is used to reconstruct the corrupted regions. The concealment strategy is embedded in the MPEG-2 decoder model in such a way that error concealment is applied after entire frame decoding. Its performance proves to be satisfactory for packet error rates (PER) ranging from 1% to 10% and for video sequences with different content and motion and surpasses that of other EC methods under study.

Content-based video parsing and indexing based on audio-visual interaction

A content-based video parsing and indexing method is presented in this paper, which analyzes both information sources (auditory and visual) and accounts for their inter-relations and synergy to extract high-level semantic information. Both frame- and object-based access to the visual information is employed. The aim of the method is to extract semantically meaningful video scenes and assign semantic label(s) to them. Due to the temporal nature of video, time has to be accounted for. Thus, time-constrained video representations and indices are generated. The current approach searches for specific types of content information relevant to the presence or absence of speakers or persons. Audio-source parsing and indexing leads to the extraction of a speaker label mapping of the source over time. Video-source parsing and indexing results in the extraction of a talking-face shot mapping over time. Integration of the audio and visual mappings constrained by interaction rules leads to higher levels of video abstraction and even partial detection of its context.

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.

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.

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.

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.

Markov chaotic sequences for correlation based watermarking schemes

Abstract In this paper, statistical analysis of watermarking schemes based on correlation detection is presented. Statistical properties of watermark sequences generated by piecewise-linear Markov maps are exploited, resulting in superior watermark detection reliability. Correlation/spectral properties of such sequences are easily controllable, a fact that affects the watermarking system performance. A family of chaotic maps, namely the skew tent map family, is proposed for use in watermarking schemes.

Embedding self-similar watermarks in the wavelet domain

A wavelet-based watermarking method for still images is presented. Watermarks are composed of scaled versions of circularly-symmetric pseudo-random 2D signals in order to attain a spatial self-similar structure with respect to a cartesian grid. Embedding and detection are performed in the wavelet domain thus allowing multi-level detection. The novelty of the method lies in the use of self-similar watermarks (quasi scale-invariant), expected to be robust against geometric transformations, especially scaling. The approach proves rather efficient against many kinds of distortions, such as linear and nonlinear filtering, JPEG and wavelet compression, scaling, cropping and rotation.

Wavelet-based self-similar watermarking for still images

This paper presents a wavelet-based watermarking method for copyright protection of still images. Watermarks are structured in such a way to attain spatial self-similarity with respect to a cartesian grid. Embedding and detection are performed in the wavelet domain thus allowing multiresolution detection. The novelty of the current approach is the use of self-similar watermarks (quasi scale-invariant), which are expected to be robust against geometric transformations, especially scaling. The approach proves rather efficient against many kinds of distortions, such as linear and nonlinear filtering, JPEG compression, scaling, cropping and rotation.