Blind Image Source Camera Identification

Abstract

Advanced imaging devices that are effective and widely available make it easier to create and control digital photographs. As a consequence it is not easier to validate the authenticity of digital images in the case of legal issues. The proposed method is an effective source examination and identification procedure for an image whose source camera is being investigated, with no prior knowledge of either the source camera or the picture. Even though Photo Response Non-Uniformity (PRNU) has acquired an incredible interest in image forensics the extraction of camera fingerprint with minimum seen content is still a challenging problem. In the proposed method fingerprint is extracted using a weighted combination of two types of de-noising filters, weighted nuclear norm minimization (WNNM) based filter and wavelet filter. A set of images captured by different mobile cameras at different locations are used as the dataset. Each image is distinct and contains different seen details having varying exposures. After the fingerprint extraction process, the fingerprints are clustered using correlation clustering followed by consensus clustering and final refinement based on their origin.