Detecting image region duplication using SIFT features

Region duplication is a common form of image manipulation where part of an image is pasted to another location to conceal undesirable contents. Most existing methods to detect region duplication are based on finding exact copies of pixel blocks, which cannot handle cases when a region is scaled or rotated before pasted to a new location. In this work, we describe a new detection method based on matching image SIFT features. The robustness of the SIFT features with regards to local transforms renders this method able to detect general region duplications with efficient computation. The effectiveness of this method is demonstrated with experimental results, both qualitatively and quantitatively in terms of the detection accuracy and the false positive rate.