Abstract
We present a method for automating the detection of the so-called JPEG ghost s. JPEG ghost s can be used for discriminating single- and double JPEG compression, which is a common cue for image manipulation detection. The JPEG ghost scheme is particularly well-suited for non-technical experts, but the manual search for such ghost s can be both tedious and error-prone. In this paper, we propose a method that automatically and efficiently discriminates single- and double-compressed regions based on the JPEG ghost principle. Experiments show that the detection results are highly competitive with state-of-the-art methods, for both, aligned and shifted JPEG grids in double-JPEG compression.
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Zach, F., Riess, C., Angelopoulou, E. (2012). Automated Image Forgery Detection through Classification of JPEG Ghosts. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_19
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DOI: https://doi.org/10.1007/978-3-642-32717-9_19
Publisher Name: Springer, Berlin, Heidelberg
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