Real-time double JPEG forensics for mobile devices
Author:
Publisher
Springer Science and Business Media LLC
Subject
Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s11554-022-01218-y.pdf
Reference33 articles.
1. Amerini, I., Uricchio, T., Ballan, L., Caldelli, R.: Localization of jpeg double compression through multi-domain convolutional neural networks. pp. 1865–1871 (2017). https://doi.org/10.1109/CVPRW.2017.233
2. Barni, M., Bondi, L., Bonettini, N., Bestagini, P., Costanzo, A., Maggini, M., Tondi, B., Tubaro, S.: Aligned and non-aligned double jpeg detection using convolutional neural networks. J. Vis. Commun. Image Represent. 49 (2017). https://doi.org/10.1016/j.jvcir.2017.09.003
3. Bas, P., Filler, T., Pevný, T.: Break our steganographic system: the ins and outs of organizing boss. In: Filler, T., Pevný, T., Craver, S., Ker, A. (eds.) Inform. Hiding, pp. 59–70. Springer, Berlin Heidelberg (2011)
4. Bianchi, T., Piva, A.: Detection of nonaligned double jpeg compression based on integer periodicity maps. IEEE Trans. Inform. Foren. Secur. 7(2), 842–848 (2012). https://doi.org/10.1109/TIFS.2011.2170836
5. Cao, G., Zhao, Y., Ni, R., Li, X.: Contrast enhancement-based forensics in digital images. IEEE Trans. Inform. Foren. Secur. 9, 515–525 (2014). https://doi.org/10.1109/TIFS.2014.2300937
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