Double compressed doctored image anti forensics with statistical forensics analysis

Abstract

The digital image information can be easily manipulated without leaving any footprints due to the availability of powerful image processing tools. Thus, there is an immediate need to confirm the legitimacy of digital images. Most of the cameras compress the image by employing Joint Photographic Experts Group (JPEG) standard. During the forgery creation, when this image is decompressed and re-compressed with different quantization matrix, it becomes double compressed doctored image. This JPEG double compression becomes an integral part of forgery creation. The detection and analysis of the historic information (for example, quantization matrix) related to JPEG compression in an image help the detective to find the truth of an image. The research work is directed to design a two-stage forensic technique to evaluate the first quantization matrix from the partial double compressed JPEG images. In the first stage of the proposed scheme, automatic isolation of the doubly compressed part from doctored image is performed by exploring the JPEG ghost technique. The second stage analyzes this doubly compressed part to estimate the first quantization matrix or steps. In the latter stage, an optimized filtering scheme is also proposed to cope with the effects of the error. The experiment results confirm that the first stage of the proposed scheme provides an average percentage accuracy of 95.45%. The second stage provides an error less than 1.5% for the first ten Discrete Cosine Transform (DCT) coefficients, hence, outperforming the existing techniques. The experimental results consider the partial double compressed images in which the recompression is done with different quantization matrix. The digital image forensics most often employs JPEG compression based forensic detectors. To confirm the capability of JPEG forensic detectors, an anti-forensic approach is desired.