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Copy-move forgery detection using improved SIFT

There are various forgeries in digital images without leaving any obvious traces of tampering due to powerful image processing and editing software. Copy-move forgery is a common type of image forgery in which a part of digital image is copied and pasted to another part in the same image with the intent of disguising some details. Based on scale invariant feature transform, a new blind detection method using Haar wavelet and ring descriptor is proposed in this paper. The method proposed not only makes the feature more stable and distinctive but also reduces the detection time dramatically. Results of experiment show that the method proposed is not only effective on different forgeries but also robust to post image processing, such as noise, blur, JPEG compression, scaling, rotation, or even compound image processing.