Copy–move forgery detection utilizing Fourier–Mellin transform log-polar features

Abstract

In this work, we address the problem of region duplication or copy–move forgery detection in digital images, along with detection of geometric transforms (rotation and rescale) and postprocessing-based attacks (noise, blur, and brightness adjustment). Detection of region duplication, following conventional techniques, becomes more challenging when an intelligent adversary brings about such additional transforms on the duplicated regions. In this work, we utilize Fourier–Mellin transform with log-polar mapping and a color-based segmentation technique using K-means clustering, which help us to achieve invariance to all the above forms of attacks in copy–move forgery detection of digital images. Our experimental results prove the efficiency of the proposed method and its superiority to the current state of the art.