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.
Highlights
Image forgery detection is attracting the attention of scientists in computer vision, digital image processing, biomedical technology, investigation, forensics, etc
This paper proposes a method which can detect the forgery in images for copy-move or splicing and for both
The proposed method is evaluated based on three different data consisting of copy-move images, spliced images and both of copy-move and splicing in the same images
Summary
Image forgery detection is attracting the attention of scientists in computer vision, digital image processing, biomedical technology, investigation, forensics, etc. With popular and complicated technologies and powerful software tools in digital images, it is difficult to confirm if the image is original or not through naked eyes (see Figure 1). This challenges researchers to develop algorithms and propose methods to detect the forgery in image. Watermarking and digital signature are solutions of information security in which a security code is inserted in the image so these methods have information of a code and the original image. A question is asked in the case if there is no code or signature inserted or information of original image, how to confirm its authenticity. Blind/passive techniques in which the detection is done in the tested image itself without any prior information are developed to solve the problem given
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