A simple and effective image-statistics-based approach to detecting recaptured images from LCD screens

It is now extremely easy to recapture high-resolution and high-quality images from LCD (Liquid Crystal Display) screens. Recaptured image detection is an important digital forensic problem, as image recapture is often involved in the creation of a fake image in an attempt to increase its visual plausibility. State-of-the-art image recapture forensic methods make use of strong prior knowledge about the recapturing process and are based on either the combination of a group of ad-hoc features or a specific and somehow complicated dictionary learning procedure. By contrast, we propose a conceptually simple yet effective method for recaptured image detection which is built upon simple image statistics and a very loose assumption about the recapturing process. The adopted features are pixel-wise correlation coefficients in image differential domains. Experimental results on two large databases of high-resolution, high-quality recaptured images and comparisons with existing methods demonstrate the forensic accuracy and the computational efficiency of the proposed method.