Abstract-A watermarking algorithm operating in the wavelet domain is presented. Performance improvement with respect to existing algorithms is obtained by means of a new approach to mask the watermark according to the characteristics of the human visual system (HVS). In contrast to conventional methods operating in the wavelet domain, masking is accomplished pixel by pixel by taking into account the texture and the luminance content of all the image subbands. The watermark consists of a pseudorandom sequence which is adaptively added to the largest detail bands. As usual, the watermark is detected by computing the correlation between the watermarked coefficients and the watermarking code, anyway the detection threshold is chosen in such a way that the knowledge of the watermark energy used in the embedding phase is not needed, thus permitting to adapt it to the image at hand. Experimental results and comparisons with other techniques operating in the wavelet domain prove the effectiveness of the new algorithm.Index Terms-Image watermarking, perceptual noise masking, wavelets.

In this paper, we propose a forensic algorithm to discriminate between original and forged regions in JPEG images, under the hypothesis that the tampered image presents a double JPEG compression, either aligned (A-DJPG) or nonaligned (NA-DJPG). Unlike previous approaches, the proposed algorithm does not need to manually select a suspect region in order to test the presence or the absence of double compression artifacts. Based on an improved and unified statistical model characterizing the artifacts that appear in the presence of both A-DJPG or NA-DJPG, the proposed algorithm automatically computes a likelihood map indicating the probability for each 8×8 discrete cosine transform block of being doubly compressed. The validity of the proposed approach has been assessed by evaluating the performance of a detector based on thresholding the likelihood map, considering different forensic scenarios. The effectiveness of the proposed method is also confirmed by tests carried on realistic tampered images. An interesting property of the proposed Bayesian approach is that it can be easily extended to work with traces left by other kinds of processing.

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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.

e aim of this survey is to provide a comprehensive overview of the state of the art in the area of image forensics. ese techniques have been designed to identify the source of a digital image or to determine whether the content is authentic or modi�ed, without the knowledge of any prior information about the image under analysis �and thus are de�ned as passive�. All these tools work by detecting the presence, the absence, or the incongruence of some traces intrinsically tied to the digital image by the acquisition device and by any other operation aer its creation. e paper has been organized by classifying the tools according to the position in the history of the digital image in which the relative footprint is le: acquisition-based methods, coding-based methods, and editing-based schemes.