At the moment, image forgery in the mainstream media has become common. The degree of manipulation is facilitated by image editing software. Hence, there are many outstanding images which have no provenance information or certainty of authenticity. Therefore, constructing a scientific and automatic way for evaluating image authenticity is an important task. In spite of having outstanding performance, all the image forensics schemes developed so far have not provided verifiable information about source of tampering. This paper aims to propose a different kind of scheme, by exploiting a group of similar images, to verify the source of tampering. We begin with slightly modifying Robert's detector to enhance the detection results. The usage of membership function used to classify the suspicious region from the authentic one is introduced as well. Inspired by the image registration concept, we exploit the correlation-based alignment method to automatically identify the spliced region in any fragment of the reference images. Although the scheme is applicable under particular conditions, the efficacy of the proposed scheme on revealing the source of spliced regions is considerable. We anticipate this scheme to be the first concrete technique toward appropriate tools which are necessary for exposing digital image forgeries.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Medical Laboratory Technology