Distinguishing between Camera and Scanned Images by Means of Frequency Analysis

  • Roberto Caldelli
  • Irene Amerini
  • Francesco Picchioni
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 8)

Abstract

Distinguishing the kind of sensor which has acquired a digital image could be crucial in many scenarios where digital forensic techniques are called to give answers. In this paper a new methodology which permits to determine if a digital photo has been taken by a camera or has been scanned by a scanner is proposed. Such a technique exploits the specific geometrical features of the sensor pattern noise introduced by the sensor in both cases and by resorting to a frequency analysis can infer if a periodicity is present and consequently which is the origin of the digital content. Experimental results are presented to support the theoretical framework.

Keywords

digital forensic source identification scanner sensor noise 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chen, M., Fridrich, J., Goljan, M., Lukas, J.: Determining Image Origin and Integrity Using Sensor Noise. IEEE Trans. on Information Forensics and Security 3(1), 74–90 (2008)CrossRefGoogle Scholar
  2. 2.
    Mondaini, N., Caldelli, R., Piva, A., Barni, M., Cappellini, V.: Detection of malevolent changes in digital video for forensic applications. In: Proc. SPIE, vol. 6505, 65050T (2007)Google Scholar
  3. 3.
    Lyu, S., Farid, H.: How realistic is photorealistic? IEEE Transactions on Signal Processing 53(2), 845–850 (2005)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Gou, H., Swaminathan, A., Wu, M.: Robust scanner identification based on noise features. In: Proc. SPIE, vol. 6505, p. 65050S (2007)Google Scholar
  5. 5.
    Swaminathan, A., Wu, M., Liu, K.J.R.: Digital Image Forensics via Intrinsic Fingerprints. IEEE Transactions on Information Forensics and Security 3(1), 101–117 (2008)CrossRefGoogle Scholar
  6. 6.
    Khanna, N., Mikkilineni, A.K., Chiu, G.T.-C., Allebach, J.P., Delp, E.J.: Scanner identification using sensor pattern noise. In: Proc. SPIE, vol. 6505, 65051K (2007)Google Scholar
  7. 7.
    Khanna, N., Chiu, G.T.-C., Allebach, J.P., Delp, E.J.: Forensic techniques for classifying scanner, computer generated and digital camera images. In: Proc. IEEE ICASSP, pp. 1653–1656 (2008)Google Scholar
  8. 8.
    Mihcak, M.K., Kozintsev, I., Ramchandran, K.: Spatially Adaptive Statistical Modeling of Wavelet Image Coefficients and its Application to Denoising. In: Proc. IEEE ICASSP, vol. 6, pp. 3253–3256 (1999)Google Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2009

Authors and Affiliations

  • Roberto Caldelli
    • 1
  • Irene Amerini
    • 1
  • Francesco Picchioni
    • 1
  1. 1.Media Integration and Communication Center - MICCUniversity of FlorenceFlorenceItaly

Personalised recommendations