Detection of Copy-Move Forgery in Images Using Segmentation and SURF

In this era of multimedia and information explosion, due to the cheap availability of software and hardware, everyone can capture, edit, and publish images, without much difficulty. Image editing done with malicious intentions known as image tampering, may affect individuals, society, economy and so on. Copy-move forgery is one of the most common and easiest image tampering method which involves copying a patch of an image and pasting it within the same image. The purpose of this may be to conceal some objects in the image or conceal the artifacts of image editing. In this paper, we propose a new method to detect copy-move tampering in images, without prior image information, using an over complete segmentation and keypoint detection. It is evident from the experimental results obtained by testing it on standard datasets, that the proposed method is tolerant to postprocessing operations like blurring, JPEG compression, noise addition and so on. Also, our method is effective in detecting copy-move forgery where copied portions are subjected to various geometric transformations, like translation, rotation and scaling.