An effective method for detecting double JPEG compression with the same quantization matrix

Jianquan YANG, Jin XIE, Guopu ZHU, Sam KWONG, Yun-Qing SHI

Research output: Journal PublicationsJournal Article (refereed)peer-review

106 Citations (Scopus)

Abstract

Detection of double JPEG compression plays an important role in digital image forensics. Some successful approaches have been proposed to detect double JPEG compression when the primary and secondary compressions have different quantization matrices. However, detecting double JPEG compression with the same quantization matrix is still a challenging problem. In this paper, an effective error-based statistical feature extraction scheme is presented to solve this problem. First, a given JPEG file is decompressed to form a reconstructed image. An error image is obtained by computing the differences between the inverse discrete cosine transform coefficients and pixel values in the reconstructed image. Two classes of blocks in the error image, namely, rounding error block and truncation error block, are analyzed. Then, a set of features is proposed to characterize the statistical differences of the error blocks between single and double JPEG compressions. Finally, the support vector machine classifier is employed to identify whether a given JPEG image is doubly compressed or not. Experimental results on three image databases with various quality factors have demonstrated that the proposed method can significantly outperform the state-of-the-art method.
Original languageEnglish
Pages (from-to)1933-1942
JournalIEEE Transactions on Information Forensics and Security
Volume9
Issue number11
Early online date19 Sept 2014
DOIs
Publication statusPublished - Nov 2014
Externally publishedYes

Keywords

  • Digital forensics
  • double JPEG compression
  • rounding error
  • truncation error

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