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,

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... espectively, in a block size 32 × 32 and 64 × 64 pixels. Subsequently, in experimental items, a classification ratio, Area Under the Curve (AUC), P TP at P 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)'. INDEX TERMS Median filtering detection (MFD) , forgery image, digital image forensics, bit-planes slicing, residual image, support vector machine (SVM).