A robust approach to detect tampering by exploring correlation patterns

Abstract

Exposing digital forgeries by detecting local correlation patterns of images has become an important kind of approach among many others to establish the integrity of digital visual content. However, this kind of method is sensitive to JPEG compression, since compression attenuates the characteristics of local correlation pattern introduced by color filter array (CFA) interpolation. Rather than concentrating on the differences between image textures, we calculate the posterior probability map of CFA interpolation with compression related Gaussian model. Thus our approach will automatically adapt to compression. Experimental results on 1000 tampered images show validity and efficiency of the proposed method. © 2011 Springer-Verlag.