LAUSR

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 ( $3\times 3$ ), averaging filtering ( $3\times 3$ ), downscaling (0.9), upscaling (1.1), and post-frame-up, respectively, in a block size $32\times 32$ and $64\times 64$ pixels. Subsequently, in experimental items, a classification ratio, Area Under the Curve (AUC), ${P} _{\mathrm {TP}}$ at ${P} _{\mathrm {FP}} =0.01$ , 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 ( ${A}$ )’.