Authors: Zhaoyi Shen Jiangqun Ni Chenglong Chen
Publish Date: 2014/12/23
Volume: 75, Issue: 4, Pages: 2327-2346
Abstract
Recently for the recovery of images’ processing history passive forensics of possible manipulations has attracted wide interest In particular due to highly nonlinearity median filtering MF usually serves as an effective tool of counter forensic techniques for other image operations Therefore the importance of median filtering detection is selfevident In this paper through analysing the pixel differences of images we found the indications to study the complex correlations introduced by median filtering and adopt two sets of describing features to measure them More Specifically we utilize a linear prediction model for the differences of image that is computed along a specific direction and estimate the prediction coefficients to construct a linear descriptor L Besides we make use of the histogram of rotation invariant local binary pattern LBP to form a nonlinear descriptor N According to our observation we also propose an enhanced feature EF to further improve the detection performance Based on these we present a novel median filtering detection scheme incorporating both the linear and nonlinear descriptors Extensive experiments are carried out which demonstrate that our proposed scheme gains favorable performance comparing to stateoftheart methods especially for low resolution images and JPEG compressed images and shows resistance to noise attackThis work is supported by National Natural Science Foundation of China No 61379156 the National Research Foundation for the Doctoral Program of Higher Education of China No 20120171110037 and the Key Program of Natural Science Foundation of Guangdong No S2012020011114
Keywords: