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Proceedings / Volume 6819 / Forensics

Camera identification from cropped and scaled images

Proc. SPIE 6819, 68190E (2008); http://dx.doi.org/10.1117/12.766732

Monday 28 January 2008
San Jose, CA, USA
Security, Forensics, Steganography, and Watermarking of Multimedia Contents X
Edward J. Delp III, Ping Wah Wong, Jana Dittmann, Nasir D. Memon
  • Abstract
Miroslav Goljan and Jessica Fridrich

SUNY Binghamton

In this paper, we extend our camera identification technology based on sensor noise to a more general setting when the image under investigation has been simultaneously cropped and scaled. The sensor fingerprint detection is formulated using hypothesis testing as a two-channel problem and a detector is derived using the generalized likelihood ratio test. A brute force search is proposed to find the scaling factor which is then refined in a detailed search. The cropping parameters are determined from the maximum of the normalized cross-correlation between two signals. The accuracy and limitations of the proposed technique are tested on images that underwent a wide range of cropping and scaling, including images that were acquired by digital zoom. Additionally, we demonstrate that sensor noise can be used as a template to reverse-engineer in-camera geometrical processing as well as recover from later geometrical transformations, thus offering a possible application for re-synchronizing in digital watermark detection.

© 2008 COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

History
Online Feb 26, 2008
Digital Object Identifier
http://dx.doi.org/10.1117/12.766732
Citation
Miroslav Goljan and Jessica Fridrich, "Camera identification from cropped and scaled images", Proc. SPIE 6819, 68190E (2008); http://dx.doi.org/10.1117/12.766732

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