• DocumentCode
    2993535
  • Title

    Blind source camera identification

  • Author

    Kharrazi, Mehdi ; Sencar, Husrev T. ; Memon, Nasir

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Eng., Polytech. Univ. Brooklyn, NY, USA
  • Volume
    1
  • fYear
    2004
  • fDate
    24-27 Oct. 2004
  • Firstpage
    709
  • Abstract
    An interesting problem in digital forensics is that given a digital image, would it be possible to identify the camera model which was used to obtain the image. In this paper we look at a simplified version of this problem by trying to distinguish between images captured by a limited number of camera models. We propose a number of features which could be used by a classifier to identify the source camera of an image in a blind manner. We also provide experimental results and show reasonable accuracy in distinguishing images from the two and five different camera models using the proposed features.
  • Keywords
    cameras; feature extraction; identification; image classification; image colour analysis; blind source camera identification; camera color characteristics; camera model identification; camera source identification; digital image forensics; feature extraction; image classification; image quality metrics; legal photographic evidence; Blood; Digital cameras; Digital forensics; Digital images; Image processing; Law enforcement; Layout; Legal factors; Manufacturing; Watermarking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2004. ICIP '04. 2004 International Conference on
  • Conference_Location
    Singapore
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-8554-3
  • Type

    conf

  • DOI
    10.1109/ICIP.2004.1418853
  • Filename
    1418853