ABSTRACT
To detect some image forgeries one can rely on the Photo-Response Non-Uniformity (PRNU), a deterministic pattern associated with each individual camera, which can be loosely modeled as low-intensity multiplicative noise. A very promising algorithm for PRNU-based forgery detection has been recently proposed by Chen et al. Image denoising is a key step of the algorithm, since it allows to single out and remove most of the signal components and reveal the PRNU pattern. In this work we analyze the influence of denoising on the overall performance of the method and show that the use of a suitable state-of-the art denoising technique improves performance appreciably w.r.t. the original algorithm.
- I.Amerini, R.Caldelli, V.Cappellini, F.Picchioni, and A.Piva. Analysis of denoising filters for photo response non uniformity noise extraction in source camera identification. In Proceedings of Digital Signal Processing, pages 1--7, Santorini, Greece, Jul. 2009. Google ScholarDigital Library
- A.Buades, B.Coll, and J.M.Morel. A review of image denoising algorithms,with a new one. Multiscale Model. Simul., 4(2):490--530. July 2005.Google ScholarCross Ref
- M.Chen, J.Fridrich, M.Goljan, and J.Luká. Determining image origin and integrity using sensor noise. IEEE Transactions on Information Forensics and Security, 3(1):74--90, Mar. 2008. Google ScholarDigital Library
- K.Dabov, A.Foi, V.Katkovnik, and K.Egiazarian. Image denoising by sparse 3D transform-domain collaborative filtering. IEEE Transactions on Image Processing, 16(8):2080--2095, Aug. 2007. Google ScholarDigital Library
- J.Fridrich. Digital image forensics. IEEE Signal Processing Magazine, 26(2):26--37, Mar. 2009.Google ScholarCross Ref
- J.Fridrich, D.Soukal, and J.Lukás. Detection of copy move forger in digital images. In Proc. Digital Forensic Research Workshop. 2003.Google Scholar
- R.G.E.Healey. Radiometric ccd camera calibration and noise estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(3):267--275, Mar. 1994. Google ScholarDigital Library
- J.He, Z.Lin, L.Wang, and X.Tang. Detecting doctored jpeg images via dct coefficient analysis. In Proc. of 9th European Conference on Computer Vision, pages 423--435, Graz, Austria, May 2006. Google ScholarDigital Library
- J.Lukas, J.Fridrich, and M.Goljan. Detecting digital image forgeries using sensor pattern noise. In SPIE Electronic Imaging Forensics, Security, Steganography, and Watermarking of Multimedia Contents VIII, volume 6072, pages 362--372, San Jose, CA, USA, Jan. 2006.Google Scholar
- M.K.Mihcak, I.Kozintsev, and K.Ramchandran. Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, pages 3253--3256, Phoenix, AZ, USA, Mar. 1999. Google ScholarDigital Library
- A.C.Popescu and H.Farid. Exposing digital forgeries by detecting duplicated image regions. Dept. Comput. sci., Dartmouth College. Tech. Rep. TR2004--515, 2004.Google Scholar
- A.C.Popescu and H.Farid. Exposing digital forgeries by detecting traces of re-sampling. IEEE Transactions on Signal Processing. 53(2):758--767, Feb. 2005. Google ScholarDigital Library
- S.Ye, Q.Sun, and E.C. Chang. Detecting digital image forgeries by measuring inconsistencies of blocking artifact. In Proc. IEEE Int. Conf. Multimedia and Expo, pages 12--15, Beijing, China, 2007.Google ScholarCross Ref
Index Terms
- On the influence of denoising in PRNU based forgery detection
Recommendations
PRNU-based Deepfake Detection
IH&MMSec '21: Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia SecurityAs deepfakes become harder to detect by humans, more reliable detection methods are required to fight the spread of fake images and videos. In our work, we focus on PRNU-based detection methods, which, while popular in the image forensics scene, have ...
Forgery detection using feature-clustering in recompressed JPEG images
JPEG images are widely used in a large range of applications. The properties of JPEG compression can be used for detection of forgery in digital images. The forgery in JPEG images requires the image to be resaved thereby, re-compression of image. ...
Detection of copy-rotate-move forgery using Zernike moments
IH'10: Proceedings of the 12th international conference on Information hidingAs forgeries have become popular, the importance of forgery detection is much increased. Copy-move forgery, one of the most commonly used methods, copies a part of the image and pastes it into another part of the the image. In this paper, we propose a ...
Comments