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Abstract: Image forensics research has mainly focused on the detection of artifacts introduced by a single processing tool, thus resulting in the development of a large number of specialized algorithms looking for one or more specific footprints under precise settings. As one may guess, the performance of such algorithms are not ideal, so the output they provide may be noisy, inaccurate and only partially true. Moreover, in real scenarios a manipulated image is often the result of the application of several tools made available by the image processing software. As a consequence, reliable tamper detection requires that several tools developed to deal with different scenarios are applied. The above observations raise two new problems: (i) deal with the uncertainty introduced by error-prone tools and (ii) devise a sound strategy to merge the information provided by the different tools into a single output. To overcome these problems we propose a decision fusion framework based on the Fuzzy Theory, which permits to cope with the uncertainty and lack of precise information typical of image forensics, by leveraging on the widely known ability of the Fuzzy Theory to deal with inaccurate and incomplete information. We describe a practical implementation of the proposed framework and validate it in a realistic scenario in which five forensic tools exploit JPEG compression artifacts to detect cut&paste tampering within a specified region of an image. The results are encouraging, and provide a significant advantage with respect to those obtained by simply OR-ing the outputs of the single tools. [Copyright &y& Elsevier]

We propose a method to improve the performance of the recently introduced rational dither modulation (RDM) watermarking scheme. The improvement is obtained by modifying the essentially scalar nature of RDM with the introduction of a vector quantiser. The vector quantiser is based on a properly modified version of classical trellis coded quantisation, thus leading to the new trellis-coded RDM scheme (TC-RDM). Due to the infinite memory of the trellis TC-RDM relies on, the standard Viterbi algorithm is no longer optimum, hence we introduce a new suboptimal encoding algorithm that keeps the computational complexity reasonably low while ensuring a minimal loss with respect to the optimal scheme. The simulations we carried out on synthetic sequences show that TC-RDM permits improvement of the performance of RDM by 2–4 dB in terms of robustness against Gaussian noise addition. [ABSTRACT FROM AUTHOR]

Research on data hiding is demonstrating every day that several applications can benefit from this technology; among these, medical data management. In particular, embedding patient information into a medical image through data hiding could improve the level of security and confidentiality that is essential for the diffusion of medical information systems. The design of a data hiding system for such an application has to take into account specific requirements, the most important are: high payload to identifying reliably a patient; quality preservation of the watermarked image; robustness to content modification. According to this analysis, a comparison between different data hiding approaches is presented, to evaluate the most suitable algorithms for embedding patient information into digital radiographs. In particular two algorithms based on statistical decision theory have been compared with schemes following the new approach of modelling data hiding as communication with side-information at the transmitter. These methods have been tested and compared in the framework of digital radiographies management in order to identify their benefits and drawbacks. [ABSTRACT FROM AUTHOR]