Copy-transform-move forgery is a simple and powerful digital image forgery technique in which a region is copied and transformed and then pasted in another position on the same image. Copy-transform-move forgery defeats all existing copy-move forgery detection methods. The high resolution of forged images brings obstacles to existing exhaustive search based detection methods. In this paper

copy-transform-move forgery of high resolution color images is studied and a detection method based on image fusion and scale-invariant feature transform(SIFT) points is proposed. Firstly

the high-resolution image is down-sampled. Secondly

the proposed method fuses the multi-channel down-sampled image information into a single gray-level image. Then a fast matching method is designed to find matching SIFT points in the fused images. The forged regions grow up stepwise based on an appropriate region growing strategy with matching SIFT points as “seed-points”. The method is tested using man-made high-resolution forgery images and doubtful news pictures. Experiment results show that the method is robust to common retouch tools

brightness adjustments and lossy compression.