An Improved Algorithm for Camera Model Identification Using Inter-channel Demosaicking Traces

Abstract

Most CFA (color filter array) interpolation-based digital image forensic methods characterize inter-pixel relationship with a linear model and use the estimated interpolation coefficients as features for image source camera identification. However, various CFA models and interpolation algorithms must be tried for coefficient estimation during the detection process in that the CFA pattern of an image is often unknown at the receiver's end. This incurs high computational complexity. Instead of using inter-pixel correlations, Ho et al. proposed to use inter-channel demosaicking/color interpolation traces for identifying the source camera model of a test image. In this work, we propose an improved algorithm. We first extract two variance maps by estimating the variances of each component of the green-to-red and green-to-blue spectrum differences, respectively, and then take the shape and texture features of these two maps for camera model identification. Experimental results show that our method achieves better overall performance.