Abstract
Many digital image forensics techniques using various fingerprints which identify the image source are dependent on data on digital images from an unknown environment. As often software modifications leave no appropriate traces in image metadata, critical miscalculations of fingerprints arise. This is the problem addressed in this paper. Modeling information noise, we introduce a statistical approach for noise-removal in databases consisted of “unguaranteed” images. In this paper, employed fingerprints are based on JPEG quantization tables.
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Mahdian, B., Saic, S., Nedbal, R. (2011). JPEG Quantization Tables Forensics: A Statistical Approach. In: Sako, H., Franke, K.Y., Saitoh, S. (eds) Computational Forensics. IWCF 2010. Lecture Notes in Computer Science, vol 6540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19376-7_13
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DOI: https://doi.org/10.1007/978-3-642-19376-7_13
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