Keypoints based copy-move forgery detection of digital images

One of the most researched areas in digital image forensics is the copy-move forgery detection where part of the image is copied and paste in the same image. This is done with a motive to either highlight a particular object or to hide or remove an object from the image. Keypoints based approach uses descriptors from specific areas on the image unlike block based methods where features are extracted from every blocks. This lead to a smaller number of descriptors and hence a faster detection algorithm can be devised using keypoints. There are number of keypoints detection algorithms available such as SIFT, SURF, GLOH etc., in this paper we are using SIFT and SURF for the purpose of feature extraction and forgery detection. We also compare the performance of the two approaches in terms of speed and accuracy. Multiple cloning of region is also taken care of using iterative method in matching.