Iwan Setyawan

Exhaustive geometrical search and the false positive watermark detection probability

One way of recovering watermarks in geometrically distorted images is by performing a geometrical search. In addition to the computational cost required for this method, this paper considers the more important problem of false positives. The maximal number of detections that can be performed in a geometrical search is bounded by the maximum false positive detection probability required by the watermark application. We show that image and key dependency in the watermark detector leads to different false positive detection probabilities for geometrical searches for different images and keys. Furthermore, the image and key dependency of the tested watermark detector increases the random-image-random-key false positive detection probability, compared to the Bernoulli experiment that was used as a model.

Low-bit-rate video watermarking using temporally extended differential energy watermarking (DEW) algorithm

Digital video data distribution through the internet is becoming more common. Film trailers, video clips and even video footage from computer and video games are now seen as very powerful means to boost sales of the aforementioned products. These materials need to be protected to avoid copyright infringement issues. However, these materials are encoded at a low bit-rate to facilitate internet distribution and this poses a challenge to the watermarking operation. In this paper we present an extension to the Differential Energy Watermarking algorithm, to use it in low bit-rate environment. We present the extension scheme and its evaluate its performance in terms of watermark capacity, robustness and visual impact.

Perceptual quality evaluation of geometrically distorted images using relevant geometric transformation modeling

One of the most active research area in the watermarking community is the research in dealing with geometric distortion. The geometric distortion problem has two aspects, namely its effect on watermark detectability and its effect on the perceptual quality of the watermarked data. Most research in this area has been concentrated on addressing the first aspect of the problem, and research on objective visual quality assessment of geometrically distorted images is not widely discussed in the literature. As a consequence, there is a lack of objective visual quality measurement for this class of distortion. In this paper we propose a method of objectively assessing the perceptual quality of geometrically distorted images. Our approach is based on the modeling of a complex, global geometric distortion using local, simpler geometric transformation models. The locality of this simpler geometric transformation determines the visual quality of the distorted images.

Human perception of geometric distortions in images

We present in this paper the results of our study on the human perception of geometric distortions in images. The ultimate goal of this study is to devise an objective measurement scheme for geometric distortions in images, which should have a good correspondence to human perception of the distortions. The study is divided into two parts. The first part of the study is the design and implementation of a user-test to measure human perception of geometric distortions in images. The result of this test is then used as a basis to evaluate the performance of the second part of the study, namely the objective quality measurement scheme. Our experiment shows that our objective quality measurement has good correspondence to the result of the user test and performs much better than a PSNR measurement.

Hiding Correlation-Based Watermark Templates using Secret Modulation

A possible solution to the difficult problem of geometrical distortion of watermarked images in a blind watermarking scenario is to use a template grid in the autocorrelation function. However, the important drawback of this method is that the watermark itself can be estimated and subtracted, or the peaks in the Fourier magnitude spectrum can be removed. A recently proposed solution is to modulate the watermark with a pattern derived from the image content and a secret key. This effectively hides the watermark pattern, making malicious attacks much more difficult. However, the algorithm to compute the modulation pattern is computationally intensive. We propose an efficient implementation, using frequency domain filtering, to make this hiding method more practical. Furthermore, we evaluate the performance of different kinds of modulation patterns. We present experimental results showing the influence of template hiding on detection and payload extraction performance. The results also show that modulating the ACF based watermark improves detection performance when the modulation signal can be retrieved sufficiently accurately. Modulation signals with small average periods between zero crossings provide the most watermark detection improvement. Using these signals, the detector can also make the most errors in retrieving the modulation signal until the detection performance drops below the performance of the watermarking method without modulation.

Complexity-scalable compensation of geometrical distortions in image watermarking

Geometrical transformations are one of the most important issues to be solved to increase the robustness of digital image watermarking systems. This paper presents an efficient method for inverting geometrical distortions that may spatially desynchronise a watermark detector. We propose a strategy that is scalable in transform complexity, since in some cases a simple transformation is sufficient to compensate the geometrical distortion while in other cases a more complex transform is needed. The strategy is implemented using an orthogonal polynomial mapping, which is efficiently scalable in complexity. To estimate the parameters of the polynomial, we use feature points. The results of the watermark detection after image registration are presented in the form of bit error rate (BER).

Relevant Modelling & Comparison of Geometric Distortions in Watermarking Systems

A challenging aspect in the development of robust watermarking algorithms is the ability to withstand complex geometric distortion of the media. A few existing techniques are known to deal with such transformations up to a certain level. Traditionally, the measure of the degradation caused by an attack on an image only addressed the pixel value modification. However, a degradation consequent to the geometric distortion of an image cannot be measured with traditional criteria. Therefore the evaluation and comparison of the robustness to desynchronization of different watermarking schemes was not possible. In this paper, we present an innovative method to measure the distortion introduced by complex geometric deformations of an image. The distortion measure is expressed in term of how closely the applied transform can be approximated by a simpler transform model (e.g. RST transform, affine transform). The scheme relies on the local least square estimation of the parameters of the reference transform model. Eventually, we illustrate the proposed measure by presenting some results for different complex image distortions.

Synchronization-insensitive Video Watermarking using Structured Noise Pattern

For most watermarking methods, preserving the synchronization between the watermark embedded in a digital data (image, audio or video) and the watermark detector is critical to the success of the watermark detection process. Many digital watermarking attacks exploit this fact by disturbing the synchronization of the watermark and the watermark detector, and thus disabling proper watermark detection without having to actually remove the watermark from the data. Some techniques have been proposed in the literature to deal with this problem. Most of these techniques employ methods to reverse the distortion caused by the attack and then try to detect the watermark from the repaired data. In this paper, we propose a watermarking technique that is not sensitive to synchronization. This technique uses a structured noise pattern and embeds the watermark payload into the geometrical structure of the embedded pattern.