An integrated technique for splicing and copy-move forgery image detection

Digital images can be easily forged with various image processing tools; nowadays the issue of digital image forgery becomes more and more important. As JPEG has been popularly used in image compression standard, forgery detection of JPEG images plays an important role now. Forging on compressed images often involves recompression and tends to erase those forging traces existed in un-compressed images. We could, however, attempt to discover new traces caused by recompression and use these traces to detect the recompressed image's forgery. The artifacts introduced by lossy JPEG compression can be regarded as an inherent feature for recompressed images. In this paper, a novel forgery image detection for splicing and copy-move forgery image is proposed. We first use a forgery image detection approach by periodicity analysis with the double compression effect in spatial and DCT domain. Then, the feature extracted by SURF descriptors is applied to resisting the variation of rotation and/or scaling. Experimental results demonstrate that the proposed technique is performed well on the detection of forgery localization. Especially for the copy-move forgery images, the proposed technique is able to locate the forged regions and recognize the non-original regions.