A coarse-to-fine copy-move image forgery detection method based on discrete cosine transform

Abstract

Copy-move forgery is a type of image forgery where one part of an image is copied and pasted in other regions of the same image, and it is one of the most common image forgeries to conceal some information in the original image. Discrete Cosine Transform (DCT) is one of the detection techniques which the detection rate relies intensely on the size of block used. Small block size is known for its ability to detect fine cloned objects, but the drawback is it produces too many false positive and requires high execution time. In this research, a method to overcome the weaknesses of using small block size by applying the coarse-to-fine approach with the two-tier process is proposed. The proposed method is evaluated on fifteen forged images on the CoMoFoD dataset. The results demonstrated that the proposed method is able to achieve high precision and recall rate of over 90% as well as improves the computation time by reducing the overall duration of forgery detection up to 73% compared to the traditional DCT method using small block size. Therefore, these findings validate that the proposed method offers a trade-off between accuracy and runtime.