Digital watermarking may be used to enforce copyright protection of digital cinema, by embedding in each projected movie an unique identifier (fingerprint). By identifying the source of illegal copies, watermarking will thus incite movie theatre managers to enforce copyright protection, in particular by preventing people from coming in with a handy cam. We propose here a non-blind watermark method to improve the watermark detection on very impaired sequences. We first present a study on the picture impairments caused by the projection on a screen, then acquisition with a handy cam. We show that images undergo geometric deformations, which are fully described by a projective geometry model. The sequence also undergoes spatial and temporal luminance variation. Based on this study and on the impairments models which follow, we propose a method to match the retrieved sequence to the original one. First, temporal registration is performed by comparing the average luminance variation on both sequences. To compensate for geometric transformations, we used paired points from both sequences, obtained by applying a feature points detector. The matching of the feature points then enables to retrieve the geometric transform parameters. Tests show that the watermark retrieval on rectified sequences is greatly improved.
Watermarking techniques have been considerably improved for the last past years, aiming at being always more resistant to attacks. In fact, if the main goal of watermarking at the beginning was to secure digital data (audio, image and video), numerous attacks are still now able to cast doubts on the owner's authenticity ; we can distinguish three different groups of attacks : these one which consist to remove the watermark, these one which aim at impairing the data sufficiently to falsify the detection, and finally these one which try to alter the detection process so that another person becomes the apparent owner of the data.
By considering the growing development of always more efficient attacks, this paper firstly presents a recent and exhaustive review of attacks in image and video watermarking. In a second part, the consequences of still image watermarking attacks on video sequences will be outlined and a particular attention will be given to the recently created benchmarks : Stirmark, the benchmark proposed by the University of Geneva Vision Group, this one proposed by the Department of Informatics of the University of Thessaloniki and finally we will speak of the current work of the European Project Certimark ; we will present a comparison of these various benchmarks and show how difficult it is to develop a self-sufficient benchmark, especially because of the complexity of intentional attacks.
KEYWORDS: Digital watermarking, Detection and tracking algorithms, Data modeling, Chemical elements, Forward error correction, Picosecond phenomena, Signal to noise ratio, Statistical modeling, Binary data, Transition metals
Watermarking can be modeled as a transmission through a steganographic channel. Most of the channels studied up to now in the literature were additive or substitutive channels where the noise modifies the data value. But other modifications may occur, as geometric distortions: images may be cropped, scaled, non-linearly distorted etc. We model such transformations by a geometric channel, where the noise modifies the geometry of the image rather than the data values. We study the jitter channel which copies and deletes randomly some lines of the image. We use a Markov chain to model the channel, and propose an algorithm to enhance the detection of a watermark embedded by a spread-spectrum technique subject to a jitter attack.
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