A hybrid copy-move image forgery detection technique based on Fourier-Mellin and scale invariant feature transforms

Abstract

In digital images, the most common forgery is copy-move image forgery in which some region(s) of an image is replicated within the image. The copy-move forgery detection (CMFD) techniques fall under two categories; keypoint-based and block-based. The keypoint-based techniques perform well under rotation and scaling but show very poor performance in the case of smooth images. On the contrary, the block-based techniques perform better in smooth images but are comparatively more time demanding. In this paper, a hybrid technique has been proposed by combining the block-based technique using Fourier-Mellin Transform (FMT) and a keypoint-based technique using Scale Invariant Feature Transform (SIFT). In this technique, the input image to be checked for forgery is first divided into texture and smooth regions. Then the keypoints are extracted from the texture part of the image using the SIFT descriptor, and the FMT is applied on the smooth part of the image. Extracted features are then matched to detect the duplicated regions of the image. The experimental results illustrate that the proposed technique performs better in comparison to other state-of-the-art CMFD techniques under various geometric transformations and post-processing operations in reasonable time.