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)'.
Highlights
In the image manipulation, the alterations are using filtering, averaging, rotating, and up-down scaling in the forgery methods
A new MF detection (MFD) scheme is proposed, in which the three kinds of the feature vector extracted from the two bit-planes and their residual of the forged image, respectively
In this paper, a new median filtering detection classifier is proposed. It used the autoregressive model as a method to extract the feature vector
Summary
The alterations are using filtering, averaging, rotating, and up-down scaling in the forgery methods. Yang et al [6] used a two-dimensional autoregressive (2D-AR) model [7] to characterize the residuals of the filtered images for the MFD This attempt seemed to have improved the low performance of the MFR AR with the combined more high-dimensional feature set, but only the. A new MFD scheme is proposed, in which the three kinds of the feature vector extracted from the two bit-planes and their residual of the forged image, respectively. Plane 1 and 8 contain the lowest and the highest order bit of all the pixels in the image, respectively This bit-planes slicing is a method to be processed in a spacial domain of the image. It considers plane 1 is a high pass filter, and plane 8 is a low pass filter, respectively
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