• DocumentCode
    3153085
  • Title

    Discriminating multiple JPEG compression using first digit features

  • Author

    Milani, Simone ; Tagliasacchi, Marco ; Tubaro, Stefano

  • Author_Institution
    Dipt. di Elettron. e Inf., Politec. di Milano, Milan, Italy
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    2253
  • Lastpage
    2256
  • Abstract
    The analysis of 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, e.g. photos uploaded on blogs, on-line albums, and photo sharing Web sites, images might be compressed several times. However, the identification of the number of compression stages applied to an image remains an open issue. This paper proposes a forensic method based on the analysis of the distribution of the first significant digits of DCT coefficients, which is modeled according to Benford´s law. The method relies on a set of Support Vector Machine (SVM) classifiers and allows us to accurately identify the number of compression stages applied to an image. Up to four consecutive compression stages were considered in the experimental validation. The proposed approach extends and outperforms the previously published methods aimed at detecting double JPEG compression.
  • Keywords
    computer forensics; data compression; image coding; support vector machines; Benford´s law; DCT coefficients; JPEG compression; compression stages; double-compressed images; first digit features; forensic method; multimedia forensics community; photo sharing Web sites; source device identification; support vector machine classifiers; Discrete cosine transforms; Image coding; Image reconstruction; Quantization; Robustness; Support vector machines; Transform coding; Benford´s law; first digit features; forgery identification; multiple JPEG compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288362
  • Filename
    6288362