Fast Computation of Sliding Discrete Tchebichef Moments and Its Application in Duplicated Regions Detection

International audienceComputational load remains a major concern when processing signals by means of sliding transforms. In this paper, we present an efficient algorithm for the fast computation of one-dimensional and two-dimensional sliding discrete Tchebichef moments. To do so, we first establish the relationships that exist between the Tchebichef moments of two neighboring windows taking advantage of Tchebichef polynomials’ properties. We then propose an original way to fast compute the moments of one window by utilizing the moment values of its previous window. We further theoretically establish the complexity of our fast algorithm and illustrate its interest within the framework of digital forensics and more precisely the detection of duplicated regions in an audio signal or an image. Our algorithm is used to extract local features of such a signal tampering. Experimental results show that its complexity is independent of the window size, validating the theory. They also exhibit that our algorithm is suitable to digital forensics and beyond to any applications based on sliding Tchebichef moments

Watermarking Techniques for Protecting Intellectual Properties in a Digital Environment

The protection and enforcement of intellectual property rights for digital media has become an important issue in many countries of the world. There is increase in the popularity and accessibility of the Internet to record, edit, replicate and broadcast multimedia content which has necessitated a high demand to protect digital information against illegal uses, manipulations and distributions. Digital watermarking technique which is the process used to embed proprietary information into multimedia digital signal provides a robust solution to this problem. This paper reviews different aspects and techniques of digital watermarking for protecting digital contents. It also explores different application areas of digital watermarking such as copyright protection, broadcast monitoring, integrity protection etc.Facultad de Informátic

Watermarking Techniques for Protecting Intellectual Properties in a Digital Environment

The protection and enforcement of intellectual property rights for digital media has become an important issue in many countries of the world. There is increase in the popularity and accessibility of the Internet to record, edit, replicate and broadcast multimedia content which has necessitated a high demand to protect digital information against illegal uses, manipulations and distributions. Digital watermarking technique which is the process used to embed proprietary information into multimedia digital signal provides a robust solution to this problem. This paper reviews different aspects and techniques of digital watermarking for protecting digital contents. It also explores different application areas of digital watermarking such as copyright protection, broadcast monitoring, integrity protection etc.Facultad de Informátic

Digital Image Watermarking in Wavelet Domain

Internet allows individuals to share the information.  The shared information is like text, image, audio and video files.  This information sharing results in some problems such as copyright violation, unauthorized use of documents. Such problems can be solved by using a technique called as digital watermarking. This paper presents different aspects of watermarking and how it is useful for intellectual property protection on internet.DOI:http://dx.doi.org/10.11591/ijece.v3i1.174

Information Hiding in Images Using Steganography Techniques

Innovation of technology and having fast Internet make information to distribute over the world easily and economically. This is made people to worry about their privacy and works. Steganography is a technique that prevents unauthorized users to have access to the important data. The steganography and digital watermarking provide methods that users can hide and mix their information within other information that make them difficult to recognize by attackers. In this paper, we review some techniques of steganography and digital watermarking in both spatial and frequency domains. Also we explain types of host documents and we focused on types of images

How Do the Hearts of Deep Fakes Beat? Deep Fake Source Detection via Interpreting Residuals with Biological Signals

Fake portrait video generation techniques have been posing a new threat to the society with photorealistic deep fakes for political propaganda, celebrity imitation, forged evidences, and other identity related manipulations. Following these generation techniques, some detection approaches have also been proved useful due to their high classification accuracy. Nevertheless, almost no effort was spent to track down the source of deep fakes. We propose an approach not only to separate deep fakes from real videos, but also to discover the specific generative model behind a deep fake. Some pure deep learning based approaches try to classify deep fakes using CNNs where they actually learn the residuals of the generator. We believe that these residuals contain more information and we can reveal these manipulation artifacts by disentangling them with biological signals. Our key observation yields that the spatiotemporal patterns in biological signals can be conceived as a representative projection of residuals. To justify this observation, we extract PPG cells from real and fake videos and feed these to a state-of-the-art classification network for detecting the generative model per video. Our results indicate that our approach can detect fake videos with 97.29% accuracy, and the source model with 93.39% accuracy.Comment: To be published in the proceedings of 2020 IEEE/IAPR International Joint Conference on Biometrics (IJCB

Fast Blind Audio Copy-Move Detection and Localization Using Local Feature Tensors in Noise

The increasing availability of audio editing software altering digital audios and their ease of use allows create forgeries at low cost. A copy-move forgery (CMF) is one of easiest and popular audio forgeries, which created by copying and pasting audio segments within the same audio, and potentially post-processing it. Three main approaches to audio copy-move detection exist nowadays: samples/frames comparison, acoustic features coherence searching and dynamic time warping. But these approaches will suffer from computational complexity and/or sensitive to noise and post-processing. In this paper, we propose a new local feature tensors-based copy-move detection algorithm that can be applied to transformed duplicates detection and localization problem to a special locality sensitive hash like procedure. The experimental results with massive online real-time audios datasets reveal that the proposed technique effectively determines and locating copy-move forgeries even on a forged speech segment are as short as fractional second. This method is also computational efficient and robust against the audios processed with severe nonlinear transformation, such as resampling, filtering, jsittering, compression and cropping, even contaminated with background noise and music. Hence, the proposed technique provides an efficient and reliable way of copy-move forgery detection that increases the credibility of audio in practical forensics application