Image Forgery Detection Based on Trigonometric Transforms

Image forgery detection is the basic key to solve many problems, especially with regard to the social problems such as those in Facebook, and court cases. Copy-move forgery is the type of forgery where a part of the image is copied to other location of the same image to hide important information or duplicate certain objects in the original image which makes the viewer suffer from difficulties to detect the forged region. In this type of image forgery, it is easy to perform forgery, but more difficult to detect it, because the features on the copied parts are similar to those of other parts of the image. This paper presents a comparison study between different trigonometric transforms in 1D and 2D for detecting the forgery parts in the image. This comparison study is based on the completeness rate and the time of processing for the detection. This comparison concludes that the DFT in 1D or 2D implementation is the best choice to detect copy-move forgery compared to other trigonometric transforms. The proposed algorithm can also be used for active forgery detection because of its robustness to detect the manipulation of digital watermarked images or images with signatures.