• DocumentCode
    3411184
  • Title

    Forensic techniques for classifying scanner, computer generated and digital camera images

  • Author

    Khanna, Nitin ; Chiu, George T -C ; Allebach, Jan P. ; Delp, Edward J.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN
  • fYear
    2008
  • fDate
    March 31 2008-April 4 2008
  • Firstpage
    1653
  • Lastpage
    1656
  • Abstract
    Digital images can be captured or generated by a variety of sources including digital cameras, scanners and computer graphics softwares. In many cases it is important to be able to determine the source of a digital image such as for criminal and forensic investigation. This paper presents methods for distinguishing between an image captured using a digital camera, a computer generated image and an image captured using a scanner. The method proposed here is based on the differences in the image generation processes used in these devices and is independent of the image content. The method is based on using features of the residual pattern noise that exist in images obtained from digital cameras and scanners. The residual noise present in computer generated images does not have structures similar to the pattern noise of cameras and scanners. The experiments show that a feature based approach using an SVM classifier gives high accuracy.
  • Keywords
    image classification; police; support vector machines; SVM classifier; classifying scanner; computer generated image; computer graphics; digital camera image; image forensics; image generation processe; pattern noise; residual pattern noise; scanner image; Digital cameras; Digital images; Forensics; Frequency estimation; Image generation; Noise reduction; Optical noise; Optical sensors; Semiconductor device noise; Support vector machines; computer graphics; digital camera; image forensics; pattern noise; scanners;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
  • Conference_Location
    Las Vegas, NV
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-1483-3
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2008.4517944
  • Filename
    4517944