2014 IEEE International Conference on Image Processing (ICIP), Paris, pp. 5322-5326.
ISSN/ISBN: Not available at this time. DOI: 10.1109/ICIP.2014.7026077
Abstract: Intrinsic statistical properties of natural uncompressed images can be used in image forensics for detecting traces of previous processing operations. In this paper, we extend the recent theoretical analysis of Benford-Fourier coefficients and propose a novel forensic detector of JPEG compression traces in images stored in an uncompressed format. The classification is based on a binary hypothesis test for which we can derive theoretically the confidence intervals, thus avoiding any training phase. Experiments on real images and comparisons with state-of-art techniques show that the proposed detector outperforms existing ones and overcomes issues due to dataset-dependency.
Bibtex:
@INPROCEEDINGS{,
author={Cecilia {Pasquini} and Fernando {P{\'e}rez-Gonz{\'a}lez} and Guilia {Boato}},
booktitle={2014 IEEE International Conference on Image Processing (ICIP)},
title={A Benford-Fourier JPEG compression detector},
year={2014},
pages={5322--5326},
doi={10.1109/ICIP.2014.7026077},
ISSN={2381-8549},
month={Oct},
url={https://ieeexplore.ieee.org/document/7026077},
}
Reference Type: Conference Paper
Subject Area(s): Image Processing