Camera identification from cropped and scaled images

Miroslav Goljan; Jessica Fridrich

doi:10.1117/12.766732

Abstract

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.

Citation Download Citation

Miroslav Goljan, Jessica Fridrich, "Camera identification from cropped and scaled images", Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190E (18 March 2008); doi: 10.1117/12.766732; https://doi.org/10.1117/12.766732

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