Abstract
To solve the problem of the false matching and low robustness in detecting copy-move forgeries, a new method was proposed in this study. It involves the following steps: first, establish a Gaussian scale space; second, extract the orientated FAST key points and the ORB features in each scale space; thirdly, revert the coordinates of the orientated FAST key points to the original image and match the ORB features between every two different key points using the hamming distance; finally, remove the false matched key points using the RANSAC algorithm and then detect the resulting copy-move regions. The experimental results indicate that the new algorithm is effective for geometric transformation, such as scaling and rotation, and exhibits high robustness even when an image is distorted by Gaussian blur, Gaussian white noise and JPEG recompression; the new algorithm even has great detection on the type of hiding object forgery.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig1_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig2_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig3_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig4_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig5_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig6_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11042-014-2431-2/MediaObjects/11042_2014_2431_Fig7_HTML.gif)
Similar content being viewed by others
References
Amerini I, Ballan L, Caldelli R et al (2011) A SIFT-based forensic method for copy–move attack detection and transformation recovery. IEEE Trans Inf Forensic Secur 6:1099–1110. doi:10.1109/TIFS.2011.2129512
Bayram S, Sencar HT, Memon N (2009) An efficient and robust method for detecting copy-move forgery. ICASSP:1053–1056. doi:10.1109/ICASSP.2009.4959768
Calonder M, Lepetit V, Strecha C et al. (2010) Brief: binary robust independent elementary features. ECCV:778–792. doi: 10.1007/978-3-642-15561-1_56
Davarzani R, Yaghmaie K, Mozaffari S et al (2013) Copy-move forgery detection using multiresolution local binary patterns. Forensic Sci Int 231:61–72. doi:10.1016/j.forsciint.2013.04.023
Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24:381–395. doi:10.1145/358669.358692
Fridrich J, Soukal BD, Lukáš AJ (2003) Detection of copy-move forgery in digital images. Proc Digit Forensic Res Work
Heinly J, Dunn E, Frahm JM (2012) Comparative evaluation of binary features. ECCV:759–773. doi: 10.1007/978-3-642-33709-3_54
Hu J, Zhang H, Gao Q (2011) An improved lexicographical sort algorithm of copy-move forgery detection. ICNDC:23–27. doi: 10.1109/ICNDC.2011.12
Huang H, Guo W, Zhang Y(2008) Detection of copy-move forgery in digital images using SIFT algorithm. PACIIA: 1241–1245. doi: 10.1109/PACIIA.2008.240
Leutenegger S, Chli M, Siegwart RY (2011) BRISK: binary robust invariant scalable keypoints. ICCV:2548–2555. doi: 10.1109/ICCV.2011.6126542
Liu G, Wang J, Lian S (2011) A passive image authentication scheme for detecting region-duplication forgery with rotation. J Netw Comput Appl 34:1557–1565. doi:10.1016/j.jnca.2010.09.001
Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60:91–110. doi:10.1023/B:VISI.0000029664.99615.94
Luo W, Huang J, Qiu G (2007) Robust detection of region-duplication forgery in digital image. ICPR 4:746–749. doi:10.1109/ICPR.2006.1003
Mahdian B, Saic S (2007) Detection of copy–move forgery using a method based on blur moment invariants. Forensic Sci Int 171:180–189. doi:10.1016/j.forsciint.2006.11.002
Muhammad G, Hussain M, Bebis G (2012) Passive copy move image forgery detection using undecimated dyadic wavelet transform. Digit Investig 9:49–57. doi:10.1016/j.diin.2012.04.004
Popescu AC, Farid H (2004) Exposing digital forgeries by detecting duplicated image regions. Dissertation, Dartmouth College
Rosin PL (1999) Measuring corner properties. Comput Vis Image Underst 73:291–307. doi:10.1006/cviu.1998.0719
Rosten E, Drummond T (2005) Fusing points and lines for high performance tracking. ICCV: 1508–1515. doi: 10.1109/ICCV.2005.104
Rosten E, Drummond T (2006) Machine learning for high-speed corner detection. ECCV:430–443. doi: 10.1007/11744023_34
Rublee E, Rabaud V, Konolige K (2011) ORB: an efficient alternative to SIFT or SURF. ICCV:2564–2571. doi: 10.1109/ICCV.2011.6126544
Ryu SJ, Lee MJ, Lee HK (2010) Detection of copy-rotate-move forgery using Zernike moments. Inf Hiding:51–65. doi: 10.1007/978-3-642-16435-4_5
Wang X, Zhang X, Li Z et al. (2011) A DWT-DCT based passive forensics method for copy-move attacks. MINES:304–308. doi: 10.1109/MINES.2011.98
Xu B, Wang J, Liu G (2010) Image copy-move forgery detection based on SURF. MINES:889–892. doi: 10.1109/MINES.2010.189
Yao H, Qiao T, Tang Z, et al. (2011) Detecting copy-move forgery using non-negative matrix factorization. MINES:591–594. doi: 10.1109/MINES.2011.104
Zhang T, Wang R (2009) Copy-move forgery detection based on SVD in digital image. ICISP:1–5. doi: 10.1109/CISP.2009.5301325
Acknowledgments
The research is partly supported by National Natural Science Foundation for young (No. 61305046).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhu, Y., Shen, X. & Chen, H. Copy-move forgery detection based on scaled ORB. Multimed Tools Appl 75, 3221–3233 (2016). https://doi.org/10.1007/s11042-014-2431-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-014-2431-2