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Many existing source camera classification methods involve either training a classifier or computing the reference pattern noise of a camera, which means a set of images of known origins have to be pre-acquired. However, such requirement can not always be satisfied in real-world forensic applications. In this work, we propose a graph based approach that(More)
Extensive studies have been carried out for detecting image forgery such as copy-move, re-sampling, blurring, and contrast enhancement. Although color modification is a common forgery technique, there is no reported forensic method for detecting this type of manipulation. In this paper, we propose a novel algorithm for estimating color modification in(More)
In digital image forensics, estimating the color filter array (CFA) pattern can be useful for digital camera identification. In this paper, we proposed the new method to estimate the CFA pattern of the digital cameras from a single image. Our method is based on the basic principal of CFA interpolation which fills an empty pixel using neighbor pixels. For(More)
As digital images have been propagated all over the world, identification techniques for image sources become more important. In this paper, we analyze properties of the scanner and find the spectral noise appeared in the frequency domain. Based on this observation, we propose a new method for identifying scanner models from scanned images. To enhance(More)
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