Forensic Detection Using Bit-Planes Slicing of Median Filtering Image

Abstract

For the detection of median filtering (MF) forensics, this paper proposes the feature vector extracted from the bit-planes slicing of the forged image. The assembled feature vector is trained in a support vector machine (SVM) classifier for the MF detection (MFD) of the forged images. The performance of the proposed MFD scheme is measured with several types of forged images: unaltered, Gaussian filtering ( 3 × 3 ), averaging filtering ( 3 × 3 ), downscaling (0.9), upscaling (1.1), and post-frame-up, respectively, in a block size 32 × 32 and 64 × 64 pixels. Subsequently, in experimental items, a classification ratio, Area Under the Curve (AUC), PTP at PFP =0.01, and Pe (a minimum average decision error) are estimated. The result in terms of AUC shows that the estimation of the proposed MFD scheme is graded as ' Excellent ( A )'.