Keypoint-based copy-move detection scheme by adopting MSCRs and improved feature matching

Copy-move detection is to find the existence of duplicated regions in an image. In this paper, an effective method based on region features is proposed to detect copy-move forgeries, especially when the image is multiple copied or with multiple copy-move groups. Firstly, maximally stable color region detector is applied to extract features, and these features are represented by Zernike moments. Then an improved matching strategy considering n best-matching features is applied to deal with the multiple-copied problem. Moreover, a hierarchical cluster algorithm is developed to estimate transformation matrices and confirm the existence of forgery. Based on these matrices, the duplicated regions can be located at pixel level. Experimental results indicate that the proposed scheme outperforms other similar state-of-the-art techniques.