Copy move forgery detection based on keypoint and patch match

Copy move has become a simple and effective operation for image forgeries due to the advancement of image editing software, which is still challenging to be detected. In this paper, a novel method is proposed for copy move forgery detection based on Keypoint and Patch Match. Local Intensity Order Pattern (LIOP), a robust keypoint descriptor, is combined with SIFT to obtain reliable keypoints. After using g2NN to match the extracted keypoints, a new matched keypoint pair description model and a density grid-based filtering strategy are applied to removing the redundancy matched keypoint pairs. Finally an enhanced patch match approach is utilized to examine the matched keypoint pairs to accurately determine the existence of forgery. Compared with the state-of-the-art methods, the proposed method can detect copy move region more precisely according to the experimental result, even when detected objects are distorted by some processing such as rotation, scaling, JPEG compression and additional noise.