A robust approach to detect tampering by exploring correlation patterns

Authors:
Lu Li;Jianru Xue;Xiaofeng Wang;Lihua Tian
Affiliations:
Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, China;Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, China;Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, China and School of science, Xi'an University of Technology, China;Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, China
Venue:
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Year:
2011

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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.