Hierarchical Categorization and Review of Recent Techniques on Image Forgery Detection

Abstract Information in the form of the image conveys more details than any other form of information. Several software packages are available to manipulate the images so that the authenticity of the images is being questioned. Several image processing approaches are available to create fake images without leaving any visual clue about the forging operation. So, proper image forgery detection tools are required to detect such forgery images. Over the past few years, several research papers were published in the digital image forensics domain for detecting fake images, thus escalating the legitimacy of the images. This survey paper attempts to review the recent approaches proposed for detecting image forgery. Accordingly, several research papers related to image forgery detection are reviewed and analyzed. The taxonomy of image forgery detection techniques is presented, and the algorithms related to each technique are discussed. The comprehensive analysis is carried out based on the dataset used, software used for the implementation and the performance achievement. Besides, the research issues associated with every approach were scrutinized together with the recommendation for future work.