Abstract: The paper presents a new method to detect forgery by copy-move, splicing or both in the same image. Multiscale, which limits the computational complexity, is used to check if there is any counterfeit in the image. By applying one-level Discrete Wavelet Transform, the sharped edges, which are traces of cut-paste manipulation, are high frequencies and detected from LH, HL and HH sub-bands. A threshold is proposed to filter the suspicious edges and the morphological operation is applied to reconstruct the boundaries of forged regions. If there is no shape produced by dilation or no highlight sharped edges, the image is not faked. In case of forgery image, if a region at the other position is similar to the defined region in the image, a copy-move is confirmed. If not, a splicing is detected. The suspicious region is extracted the feature using Run Difference Method (RDM) and a feature vector is created. Searching regions having the same feature vector is called detection phase. The algorithm applying multiscale and morphological operation to detect the sharped edges and RDM to extract the image features is simulated in Matlab with high efficiency not only in the copy-move or spliced images but also the image with both copy-move and splicing.
Keywords: Forgery detection (FD); Copy-Move; Discrete Wavelet Transform (DWT); Run Difference Method (RDM); Splicing, Sharpness