We introduce an isotopic measure of local contrast for natural images that is based on analytic filters and present the design of directional wavelet frames suitable for its computation. We show how this contrast measure can be used within a masking model to facilitate the insertion of a watermark in an image while minimizing visual distortion.
KEYWORDS: Digital watermarking, Distortion, Visualization, Image quality, Image compression, Signal to noise ratio, Image processing, Databases, Image analysis, Digital imaging
Research in digital watermarking has progressed along two paths. While new watermarking technologies are being developed, some researchers are also investigating different ways of attacking digital watermarks. Common attacks to watermarks usually aim to destroy the embedded watermark or to impair its detection. In this paper we propose a conceptually new attack for digitally watermarked images. The proposed attack does not destroy an embedded watermark, but copies it from one image to a different image. Although this new attack does not destroy a watermark or impair its detection, it creates new challenges, especially when watermarks are used for copyright protection and identification. The process of copying the watermark requires neither algorithmic knowledge of the watermarking technology nor the watermarking key. The attack is based on an estimation of the embedded watermark in the spatial domain through a filtering process. The estimate of the watermark is then adapted and inserted into the target image. To illustrate the performance of the proposed attack we applied it to commercial and non-commercial watermarking schemes. The experiments showed that the attack is very effective in copying a watermark from one image to a different image. In addition, we have a closer look at application dependent implications of this new attack.
KEYWORDS: Digital watermarking, Visualization, Distortion, Image compression, Image quality, Image processing, Signal to noise ratio, Databases, Digital imaging, Nonlinear filtering
Since the early 90s a number of papers on 'robust' digital watermarking systems have been presented but none of them uses the same robustness criteria. This is not practical at all for comparison and slows down progress in this area. To address this issue, we present an evaluation procedure of image watermarking systems. First we identify all necessary parameters for proper benchmarking and investigate how to quantitatively describe the image degradation introduced by the watermarking process. For this, we show the weaknesses of usual image quality measures in the context watermarking and propose a novel measure adapted to the human visual system. Then we show how to efficiently evaluate the watermark performance in such a way that fair comparisons between different methods are possible. The usefulness of three graphs: 'attack vs. visual-quality,' 'bit-error vs. visual quality,' and 'bit-error vs. attack' are investigated. In addition the receiver operating characteristic (ROC) graphs are reviewed and proposed to describe statistical detection behavior of watermarking methods. Finally we review a number of attacks that any system should survive to be really useful and propose a benchmark and a set of different suitable images.
In this paper, benchmarking results of watermarking techniques are presented. The benchmark includes evaluation of the watermark robustness and the subjective visual image quality. Four different algorithms are compared, and exhaustively tested. One goal of these tests is to evaluate the feasibility of a Common Functional Model (CFM) developed in the European Project OCTALIS and determine parameters of this model, such as the length of one watermark. This model solves the problem of image trading over an insecure network, such as Internet, and employs hybrid watermarking. Another goal is to evaluate the resistance of the watermarking techniques when subjected to a set of attacks. Results show that the tested techniques do not have the same behavior and that no tested methods has optimal characteristics. A last conclusion is that, as for the evaluation of compression techniques, clear guidelines are necessary to evaluate and compare watermarking techniques.
In this paper we propose a new watermarking scheme for digital images that allows watermark recovery even if the image has been subjected to generalized geometrical transforms. The watermark is given by a binary number and every watermark bit is represented by a 2D function. The functions are weighted, using a mask that is proportional to the luminance, and then modulated onto the blue component of the image. To recover an embedded bit, the embedded watermark is estimated using a prediction filter. The sign of the correlation between the estimated watermark and the original function determine the embedded several times at horizontally and vertically shifted locations. In the watermark recovery process we first compute a prediction of the embedded watermark. Then the autocorrelation function is computed for this prediction. The multiple embedding of the watermark result in additional autocorrelation peaks. By comparing the configuration of the extracted peaks with their expected configuration we can determine the affine distortion applied to the image. The distortion can then be inverted and the watermark recovered in a standard way.
Watermarking techniques, also referred to as digital signature, sign images by introducing changes that are imperceptible to the human eye but easily recoverable by a computer program. Generally, the signature is a number which identifies the owner of the image. The locations in the image where the signature is embedded are determined by a secret key. Doing so prevents possible pirates from easily removing the signature. Furthermore, it should be possible to retrieve the signature from an altered image. Possible alternations of signed images include blurring, compression and geometrical transformations such as rotation and translation. These alterations are referred to as attacks. A new method based on amplitude modulation is presented. Single signature bits are multiply embedded by modifying pixel values in the blue channel. These modifications are either additive or subtractive, depending on the value of the bit, and proportional to the luminance. This new method has shown to be resistant to both classical attacks, such as filtering, and geometrical attacks. Moreover, the signature can be extracted without the original image.
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