A bibliography of pixel-based blind image forgery detection techniques

With the advent of powerful image editing tools, manipulating images and changing their content is becoming a trivial task. Now, you can add, change or delete significant information from an image, without leaving any visible signs of such tampering. With more than several millions pictures uploaded daily to the net, the move towards paperless workplaces, and the introduction of e-Government services everywhere, it is becoming important to develop robust detection methods to identify image tampering operations and validate the credibility of digital images. This led to major research efforts in image forensics for security applications with focus on image forgery detection and authentication. The study of such detection techniques is the main focus of this paper. In particular, we provide a comprehensive survey of different forgery detection techniques, complementing the limitations of existing reviews in the literature. The survey covers image copy-move forgery, splicing, forgery due to resampling, and the newly introduced class of algorithms, namely image retouching. We particularly discuss in detail the class of pixel-based techniques which are the most commonly used approaches, as these do not require any a priori information about the type of tampering. The paper can be seen as a major attempt to provide an up-to-date overview of the research work carried in this all-important field of multimedia. HighlightsA new comprehensive survey of pixel-based forgery detection methods is presented.A framework for grouping different forgery detection algorithms is described.We outline the strengths and weaknesses of research efforts in forgery detection.Numerous tables and figures, analyzing existing algorithms, are discussed.An extensive list of references covering the work of the last decade is provided.