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Discriminating multiple JPEG compressions using first digit features

  • Simone Milani (a1), Marco Tagliasacchi (a1) and Stefano Tubaro (a1)
Abstract

The analysis of JPEG double-compressed images is a problem largely studied by the multimedia forensics community, as it might be exploited, e.g., for tampering localization or source device identification. In many practical scenarios, like photos uploaded on blogs, on-line albums, and photo sharing web sites, images might be JPEG compressed several times. However, the identification of the number of compression stages applied to an image remains an open issue. We proposes a forensic method based on the analysis of the distribution of the first significant digits of the discrete cosine transform coefficients, which follow Benford's law in images compressed just once. Then, the detector is optimized and extended in order to identify accurately the number of compression stages applied to an image. The experimental validation considers up to four consecutive compression stages and shows that the proposed approach extends and outperforms the previously-published algorithms for double JPEG compression detection.

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Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
Corresponding author: S. Milani simone.milani@polimi.it
Linked references
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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

[1] A. Piva : An overview on image forensics. ISRN Signal Processing, 2013, 2013, article ID 496701.

[5] G. Wallace : The JPEG Still Picture Compression Standard, Commun. ACM, 34 (4) (1991), 3044.

[8] F. Galvan ; G. Puglisi ; A.R. Bruna ; S. Battiato : First quantization matrix estimation from double compressed JPEG images. IEEE Trans. Inf. Forensics Security, 9 (8) (2014) 12991310.

[11] E.Y. Lam ; J.W. Goodman : A mathematical analysis of the DCT coefficient distributions for images. IEEE Trans. Image Process., 9 (10) (2000) 16611666.

[13] Z. Lin ; J. He ; X. Tang ; C.-K. Tang : Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis. Pattern Recognit., 42 (11) (2009) 24922501.

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APSIPA Transactions on Signal and Information Processing
  • ISSN: 2048-7703
  • EISSN: 2048-7703
  • URL: /core/journals/apsipa-transactions-on-signal-and-information-processing
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