Image forgery localization using fine grained analysis of CFA artifacts

Abstract: The usage of low-cost and high-resolution digital cameras and sophisticated photo editing software, digital images can be easily manipulated and altered. This project Image Forgery Localization using Fine-Grained Analysis of CFA Artifacts, a forensic tool, which able to discriminate between original and forged regions in an image captured by a digital camera. Most digital cameras employ a single sensor in conjunction with a color filter array (CFA). The assumption that the image is acquired using a Color Filter Array, and that tampering removes the artifacts due to the demosaicking algorithm. Then interpolate the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed during tampering. This method is based on a new feature measuring the presence of demosaicking artifacts at a local level and on a new statistical model allowing deriving the tampering probability of each 2X2 image block without requiring a priori knowledge about the position of the forged region. Proposed method reduces error lavel to 19% and gives the Structural similarity of 98%.

Keywords: CFA artifacts, demosaicking, probability map, image tampering detection.