Image Forgery and Detection of Copy Move Forgery in Digital Images: A Survey of Recent Forgery Detection Techniques

Abstract

With the development of Image processing editing tools and software, an image is manipulated very easily. The image manipulation detection is essential for the reason that an image can be employed as legal evidence, in the field of forensics investigations, and also in numerous various other fields. The image forgery detection based on pixels aims to validate the digital image authenticity with no aforementioned information of the main image. There are several means intended for tampering a digital image, for example, copymove or splicing, resampling a digital image (stretch, rotate, resize), removal as well as the addition of an object from your image. Copy move image forgery detection is utilized to figure out the replicated regions as well as the pasted parts, however forgery detection may possibly vary dependant on whether or not there is virtually any post-processing on the replicated part before inserting the item completely to another party. Typically, counterfeiters utilize many operations like rotation, filtering, JPEG compression, resizing as well as the addition of noise to the main image before pasting, that make this thing challenging to recognize the copy move image forgery. Hence, forgery detector needs to be robust to any or all manipulations and also the latest editing software tools. In the literature part, various researchers portrayed the working scenario of copy-move image forgery utilizing the similarity measures as well as the relationship among the original parts of the image and their pasted parts in the similar image. This research paper illustrates recent issues in the techniques of forgery detection and also all their comparative analysis.