18 March 2008 Camera identification from cropped and scaled images
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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.
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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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