Patch-match based detection of copy-move forgeries using rotation invariant features

Abstract

As society increasingly relies on computers and digital data, the judiciary and other businesses are highly dependent on digital forensics for identification, preservation, examination and analysis of digital evidence such as digital photographs and digital documents. The wide range of powerful image editing tools that are evolving day by day helps to modify the image content, or to tamper the image with ease and does not require any expertise. The most challenging form of tampering to be detected is the copy – move forgery. The process of tampering images by copying one portion of the and pasting it in some other region of the same image is referred to as copy-move forgery. To make the copy-move forgery detection problem further complex, variations like scaling, rotation, flipping, etc. may be made over the copied region before it is pasted. Even those of us with the sharpest eyes may easily be fooled with such fake images and this is one of the major problems in courtrooms and in press publications. As such the integrity as well of authenticity of images is highly important where decision making or judgements have to be made based on the information obtained through images.Rotation- invariant features computed densely on the image and patch-match algorithm is proposed in this paper, to detect copy-move forgeries. The proposed detection algorithm is executed in three steps. Firstly, Circular Harmonic Transform based rotation invariant Zernike Moment and FMT features are computed for each pixel of interest. Secondly matching of dense features, is carried out using patch matching algorithm and finally post-processing is carried out to minimize the false positives. Experimental results demonstrate that the proposed approach is efficient in detecting copy move forgeries subjected to various types of geometric distortions.