The growing use of digital images in a wide range of applications, and growing the availability of many editing photo software, cause to emerge a challenge to discover the images tampering. In this paper, we proposed a method to detect the most important type of forgery image (copy and move). We suggested many steps to classify the image as forgery or non-forgery image, started with preprocessing (included, convert image to gray image, de-noising, and image resize). Then, the image will be divided into several overlapping blocks. For each block, feature extracted (used it as a matching feature) by using the singular value decomposition (SVD) transformation. According to these features, the pixels were collected in many main groups, and then these groups clustered to many subgroups. The weight for each main group can be determined by comparing the subgroups with each other according to suggested conditions. The number of subgroups and weights are used to classify images to forgery or non-forgery images. The accuracy of detection and classified the forgery images were up to 97%. The suggested method is robust for tampered object rotation, scaling, and change of illumination.
On the security of ownership watermarking of digital images based on singular value decomposition
