In this paper, a forensic tool able to discriminate between original and forged regions in an image captured by a digital camera is presented. We make the assumption that the image is acquired using a Color Filter Array, and that tampering removes the artifacts due to the demosaicing algorithm. The proposed method is based on a new feature measuring the presence of demosaicing artifacts at a local level, and on a new statistical model allowing to derive the tampering probability of each 2 × 2 image block without requiring to know a priori the position of the forged region. Experimental results on different cameras equipped with different demosaicing algorithms demonstrate both the validity of the theoretical model and the effectiveness of our scheme.
Watermark detection, i.e., the detection of an invisible signal hidden within an image for copyright protection or data authentication, has classically been tackled by means of correlation-based techniques. Nevertheless, when watermark embedding does not obey an additive rule, or when the features the watermark is superimposed on do not follow a Gaussian pdf, correlation-based decoding is not the optimum choice. A new decoding algorithm is presented here which is optimum for nonadditive watermarks embedded in the magnitude of a set of full-frame DFT coefficients of the host image. By relying on statistical decision theory, the structure of the optimum is derived according to the Neyman-Pearson criterion, thus permitting to minimize the missed detection probability subject to a given false detection rate. The validity of the optimum decoder has been tested thoroughly to assess the improvement it permits to achieve from a robustness perspective. The results we obtained confirm the superiority of the novel algorithm with respect to classical correlation-based decoding.
This work addresses the problem of optimum decoding and detection of a multibit, multiplicative watermark hosted by Weibull-distributed features: a situation which is classically encountered for image watermarking in the magnitude-of-DFT domain. As such, this work can be seen as an extension of the system described in a previous paper, where the same problem is addressed for the case of 1-bit watermarking. The theoretical analysis is validated through Monte Carlo simulations. Although the structure of the optimum decoder/detector is derived in the absence of attacks, some experimental results are also presented, giving a measure of the overall robustness of the watermark when attacks are present
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