A survey on image tampering and its detection in real-world photos

Abstract Editing a real-world photo through computer software or mobile applications is one of the easiest things one can do today before sharing the doctored image on one’s social networking sites. Although most people do it for fun, it is suspectable if one concealed an object or changed someone’s face within the image. Before questioning the intention behind the editing operations, we need to first identify how and which part of the image has been manipulated. It therefore demands automatic tools for identifying the intrinsic difference between authentic images and tampered images. This survey provides an overview on typical image tampering types, released image tampering datasets and recent tampering detection approaches. It presents a distinct perspective to rethink various assumptions of tampering clues behind different detection approaches. And this further encourages the research community to develop general tampering localization methods in the future instead of adhering to single-type tampering detection.