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Duplicated Region Detection Using Robust Features
Region duplication is a common form of image forgery in which a part of digital image is copied and moved to another part of the same image in order to conceal some important objects. At present, most of the detection algorithm is based on the pixel block matching or the match transforms domain coefficients. However, the detection method becomes invalid when the duplicated regions suffer post processing, such as geometrical or illumination distortions. This paper aims to design a novel scheme that is robust to noise pollution and geometrical distortions of duplicated regions, by using speed-up robust feature (SURF) key-points, which are insensitive to geometrical and illumination distortions. Firstly, SURF key-points are found out; secondly, they are matched with each other. With the matched key-point pairs, one can estimate the affine transform matrix which is critical to locate the tempered area; finally, the tempered area can be detected by morphological operation. Experiment results show that the proposed method outperforms existing methods. The proposed algorithm can detect duplicated regions even the tempered image suffering from the post-processing, including rotate, scale, noise contamination, and jpeg-compression.
Image forensics, region duplication, affine-transform, Speeded up Robust Feature.
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