We address the known problem of detecting a previous compression in JPEG images, focusing on the challenging case of high and very high quality factors (>= 90) as well as repeated compression with identical or nearly identical quality factors. We first revisit the approaches based on Benford--Fourier analysis in the DCT domain and block convergence analysis in the spatial domain. Both were originally conceived for specific scenarios. Leveraging decision tree theory, we design a combined approach complementing the discriminatory capabilities. We obtain a set of novel detectors targeted to high quality grayscale JPEG images.

Forensics of high quality and nearly identical JPEG image recompression

Cecilia Pasquini;
2016-01-01

Abstract

We address the known problem of detecting a previous compression in JPEG images, focusing on the challenging case of high and very high quality factors (>= 90) as well as repeated compression with identical or nearly identical quality factors. We first revisit the approaches based on Benford--Fourier analysis in the DCT domain and block convergence analysis in the spatial domain. Both were originally conceived for specific scenarios. Leveraging decision tree theory, we design a combined approach complementing the discriminatory capabilities. We obtain a set of novel detectors targeted to high quality grayscale JPEG images.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/359240
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