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

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Author(s)

  • Jianquan Yang
  • Jin Xie
  • Guopu Zhu
  • Sam Kwong
  • Yun-Qing Shi

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number6905821
Pages (from-to)1933-1942
Journal / PublicationIEEE Transactions on Information Forensics and Security
Volume9
Issue number11
Online published19 Sep 2014
Publication statusPublished - Nov 2014

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.

Research Area(s)

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

Citation Format(s)