Nowadays, sophisticated computer graphics editors lead to a significant increase in the photorealism of images.
Thus, computer generated (CG) images result to be convincing and hard to be distinguished from real ones at
a first glance. Here, we propose an image forensics technique able to automatically detect local forgeries, i.e.,
objects generated via computer graphics software inserted in natural images, and vice versa. We develop a novel
hybrid classifier based on wavelet based features and sophisticated pattern noise statistics. Experimental results
show the effectiveness of the proposed approach.