Showing papers by "Thierry Pun published in 2001"

Attacks on digital watermarks: classification, estimation based attacks, and benchmarks

Abstract: Watermarking is a potential method for protection of ownership rights on digital audio, image, and video data. Benchmarks are used to evaluate the performance of different watermarking algorithms. For image watermarking, the Stirmark package is the most popular benchmark, and the best current algorithms perform well against it. However, results obtained by the Stirmark benchmark have to be handled carefully since Stirmark does not properly model the watermarking process and consequently is limited in its potential for impairing sophisticated image watermarking schemes. In this context, the goal of this article is threefold. First, we give an overview of the current attacking methods. Second, we describe attacks exploiting knowledge about the statistics of the original data and the embedded watermark. We propose a stochastic formulation of estimation-based attacks. Such attacks consist of two main stages: watermark estimation, exploitation of the estimated watermark to trick watermark detection or create ownership ambiguity. The full strength of estimation-based attacks can be achieved by introducing additional noise, where the attacker tries to combine the estimated watermark and the additive noise to impair watermark communication as much as possible while fulfilling a quality constraint on the attacked data. With a sophisticated quality constraint it is also possible to exploit human perception: the human auditory system in case of audio watermarks and the human visual system in case of image and video watermarks. Third, we discuss the current status of image watermarking benchmarks. We present Petitcolas'(see Electronic Imaging '99: Security and Watermarking of Multimedia Content, SPIE Proc., vol.3657, San Jose, CA, 1999) Stirmark benchmarking tool. Next, we consider the benchmark proposed by the University of Geneva Vision Group that contains more deliberate attacks. Finally, we summarize the current work of the European Certimark project, whose goal is to accelerate efforts from a number of research groups and companies in order to produce an improved ensemble of benchmarking tools.

Second Generation Benchmarking and Application Oriented Evaluation

Abstract: Digital image watermarking techniques for copyright protection have become increasingly robust. The best algorithms perform well against the now standard benchmark tests included in the Stirmark package. However the stirmark tests are limited since in general they do not properly model the watermarking process and consequently are limited in their potential to removing the best watermarks. Here we propose a second generation benchmark for image watermarking which includes attacks which take into account powerful prior information about the watermark and the watermarking algorithms. We follow the model of the Stirmark benchmark and propose several new categories of tests including: denoising (ML and MAP), wavelet compression, watermark copy attack, active desynchronization, denoising, geometrical attacks, and denoising followed by perceptual remodulation. In addition, we take the important step of presenting results as a function of application. This is an important contribution since it is unlikely that one technology will be suitable for all applications.

Multibit digital watermarking robust against local nonlinear geometrical distortions

Abstract: This paper presents an efficient method for the estimation and recovering from nonlinear or local geometrical distortions, such as the random bending attack and restricted projective transforms. The distortions are modeled as a set of local affine transforms, the watermark being repeatedly allocated into small blocks in order to ensure its locality. The estimation of the affine transform parameters is formulated as a robust penalized maximum likelihood (ML) problem, which is suitable for the local level as well as for global distortions. Results with the Stirmark benchmark confirm the high robustness of the proposed method and show its state-of-the-art performance.

Optimal adaptive diversity watermarking with channel state estimation

Abstract: This work advocates the formulation of digital watermarking as a communication problem. We consider watermarking as communication with side information available for both encoder and decoder. A generalized watermarking channel is considered that includes geometrical attacks, fading and additive non-Gaussian noise. The optimal encoding/decoding scenario is discussed for the generalized watermarking channel.

Automated benchmarking in content-based image retrieval

Abstract: Benchmarking has always been a crucial problem in content-based image retrieval (CBIR). A key issue is the lack of a common access method to retrieval systems, such as SQL for relational databases. The Multimedia Retrieval Mark-up Language (MRML) solves this problem by standardizing access to CBIR systems (CBIRSs). Other difficult problems are also shortly addressed, such as obtaining relevance judgments and choosing a database for performance comparison. In this article we present a fully automated benchmark for CBIRSs based on MRML, which can be adapted to any image database and almost any kind of relevance judgment. The test evaluates the performance of positive and negative relevance feedback, which can be generated automatically from the relevance judgments. To illustrate our purpose, a freely available, non-copyright image collection is used to evaluate our CBIRS, Viper. All scripts described here are also freely available for download.

An audio-haptic tool for non-visual image representation

Abstract: This paper reports on the design of an audio-haptic tool that enables blind computer users to explore a picture by the hearing and feeling modalities. The tool is divided in two entities: a description tool and an exploration tool. The description tool allows moderators (sighted person) to describe a scene. Therefore, the scene is firstly segmented manually or automatically into a set of objects (car, tree, house, etc.). For. every object, the moderator can define a behavior which correspond either to an auditory (i.e., using speech or non-speech sound) or to a kinesthetic rendering. The blind person uses the exploration tool in order to obtain the audio-haptic rendering of the segmented image previously defined by the moderator. Depending on the nature of the feedback defined (audio, kinesthetic), the blind user interacts either with a graphic tablet and/or a force feedback device.

Design and evaluation of a content-based image retrieval system

Abstract: The growth in size and accessibility of multimedia databases have changed our approach to information retrieval. Classical text-based systems show their limitations in the context of multimedia retrieval. In this chapter, we address the problem of conceiving and evaluating a content-based image retrieval system. First, we investigate the use of the query-by-example (QBE) paradigm as a base paradigm for the development of a content-based image retrieval system (CBIRS). We show that it should be considered as a complement to the classical textual-based paradigms. We then evaluate the capabilities of the most up-to-date computer vision techniques in contributing to the realisation of such a system. Further, beyond the necessity of accurate image understanding techniques, we show that the amount of data involved by the process of describing image content should also be considered as an important issue. This aspect of our study is largely based on the experience acquired by the text retrieval (TR) community, which we adapt to the context of CBIR. Similarly, the text retrieval community has also developed a significant experience in evaluating retrieval systems, where judgements include subjectivity and context dependency. Extending this experience, we study a coherent framework for performing the evaluation of a CBIRS. As a practical example, we use our Viper CBIR system, using a novel communication protocol called MRML to pinpoint the importance of the sharing of resource in facilitating the evaluation and therefore the development of CBIRS.

Blur/Deblur Attack against Document Protection Systems Based on Digital Watermarking

Abstract: A growing concern emerges regarding the possibility of counterfeiting currencies using digital imaging technologies. In order to help developing resistance against this new type of fraud, this paper presents possible attacking scenarios against supposedly sophisticated document protection systems based on digital watermarking. These new attacks, which would allow even an average counterfeiter to reproduce banknotes or passports created using systems with built-in watermark detector.

Evaluating image browsers using structured annotation

Abstract: In this article we address the problem of benchmarking image browsers. Image browsers are systems that help the user in finding an image from scratch, as opposed to query by example (QBE), where an example image is needed. The existence of different search paradigms for image browsers makes it difficult to compare image browsers. Currently, the only admissible way of evaluation is by conducting large-scale user studies. This makes it difficult to use such an evaluation as a tool for improving browsing systems. As a solution, we propose an automatic image browser benchmark that uses structured text annotation of the image collection for the simulation of the user's needs. We apply such a benchmark on an example system.