Detecting doctored images using camera response normality and consistency

The advance in image/video editing techniques has facilitated people in synthesizing realistic images/videos that may hard to be distinguished from real ones by visual examination. This poses a problem: how to differentiate real images/videos from doctored ones? This is a serious problem because some legal issues may occur if there is no reliable way for doctored image/video detection when human inspection fails. Digital watermarking cannot solve this problem completely. We propose an approach that computes the response functions of the camera by selecting appropriate patches in different ways. An image may be doctored if the response functions are abnormal or inconsistent to each other. The normality of the response functions is classified by a trained support vector machine (SVM). Experiments show that our method is effective for high-contrast images with many textureless edges.