Abstract
In this paper, we propose a novel approach for source camera identification based on camera gain histogram. By using the photon transfer curve (PTC) as camera noise model, we construct camera gain histogram from the occurrences of different camera gain constants. With the distribution of camera gain histogram for each camera, we extract four features to characterize the camera. In our experiments, 400 photos acquired from two high-end digital cameras at two different exposure levels are used to evaluate the effectiveness of the proposed approach. A two-class support vector machine (SVM) is employed as a classifier. Our experimental results demonstrate that the distinction rate in identifying different cameras achieves promising performance. © 2007 IEEE.