Improved DCT-based detection of copy-move forgery in images

Abstract Techniques for digital image tampering are becoming more and more sophisticated and widespread. Copy-move forgery is one of the tampering techniques that are frequently used. In this paper, an improved DCT-based method is developed to detect this specific artifact. Firstly, the image is divided into fixed-size overlapping blocks and, DCT is applied to each block to represent its features. Truncating is employed to reduce the dimension of the features. Then the feature vectors are lexicographically sorted and, duplicated image blocks will be neighboring in the sorted list. Thus duplicated image blocks will be compared in the matching step. To make the method more robust, a scheme to judge whether two feature vectors are similar is imported. Experiment results demonstrated that the proposed method can detect the duplicated regions even when an image was distorted by JPEG compression, blurring or additive white Gaussian noise.