Digital Image Forensics: A Two-Step Approach for Identifying Source and Detecting Forgeries

Digital Image Forensics includes two main domains: source device identification and semantic modification detection. Usually, existing works address one aspect only: either source identification or either image manipulation. In this article, we investigate a new approach based on sensor noise that operates in a two-step sequence: the first one is global whereas the second one is local. During the first step, we analyze noise in order to identify the sensor. We reused the method proposed by Jessica Fridrich et al. with an improvement of it useful when only a limited number of images is available to compute noise patterns. Then, having identified the sensor, we examine more locally, using quadtree segmentation, the noise differences between the pattern noise attached to the sensor and the noise extracted from the picture under investigation in order to detect possible alterations. We assume here that the portion of the image that underwent modifications is relatively small with regards to the surface of the whole picture. Finally, we report tests on the first publically available database (i.e. the Dresden database) that makes possible further comparisons of our algorithm with other approaches.