|Table of Contents|

[1] Chen Beijing, , Gao Ye, et al. An effective copy-move forgery detection algorithm using fractionalquaternion Zernike moments and improved PatchMatch algorithm [J]. Journal of Southeast University (English Edition), 2019, 35 (4): 431-439. [doi:10.3969/j.issn.1003-7985.2019.04.005]
Copy

An effective copy-move forgery detection algorithm using fractionalquaternion Zernike moments and improved PatchMatch algorithm()
Share：

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
35
Issue:
2019 4
Page:
431-439
Research Field:
Computer Science and Engineering
Publishing date:
2019-12-30

Info

Title:
An effective copy-move forgery detection algorithm using fractionalquaternion Zernike moments and improved PatchMatch algorithm
Author(s):
Chen Beijing1;  2;  3;  Gao Ye1;  Yu Ming1;  Wu Peng1;  Shu Huazhong4
1School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
2Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
3Key Laboratory of Computer Network Technology of Jiangsu Province, Southeast University, Nanjing 210096, China
4Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China
Keywords:
quaternion;  fractional Zernike moments;  PatchMatch algorithm;  copy-move forgery detection
PACS:
TP391
DOI:
10.3969/j.issn.1003-7985.2019.04.005
Abstract:
An effective algorithm is proposed to detect copy-move forgery. In this algorithm, first, the PatchMatch algorithm is improved by using a reliable order-statistics-based approximate nearest neighbor search algorithm(ROSANNA)to modify the propagation process. Then, fractional quaternion Zernike moments(FrQZMs)are considered to be features extracted from color forged images. Finally, the extracted FrQZMs features are matched by the improved PatchMatch algorithm. The experimental results on two publicly available datasets(FAU and GRIP datasets)show that the proposed algorithm performs better than the state-of-the-art algorithms not only in objective criteria F-measure value but also in visual. Moreover, the proposed algorithm is robust to some attacks, such as additive white Gaussian noise, JPEG compression, rotation, and scaling.

References:

[1] Fridrich A J, Soukal B D, Lukáš J. Detection of copy-move forgery in digital images[C]// Proceedings of Digital Forensic Research Workshop. Cleveland, OH, USA, 2003:1-10.
[2] Sitara K, Mehtre B M. Digital video tampering detection: An overview of passive techniques[J]. Digital Investigation, 2016, 18: 8-22. DOI:10.1016/j.diin.2016.06.003.
[3] Christlein V, Riess C, Jordan J, et al. An evaluation of popular copy-move forgery detection approaches[J]. IEEE Transactions on Information Forensics and Security, 2012, 7(6): 1841-1854. DOI:10.1109/tifs.2012.2218597.
[4] Bi X L, Pun C M. Fast reflective offset-guided searching method for copy-move forgery detection[J]. Information Sciences, 2017, 418/419: 531-545. DOI:10.1016/j.ins.2017.08.044.
[5] Lee J C, Chang C P, Chen W K. Detection of copy-move image forgery using histogram of orientated gradients[J]. Information Sciences, 2015, 321: 250-262. DOI:10.1016/j.ins.2015.03.009.
[6] Bi X L, Pun C M, Yuan X C. Multi-level dense descriptor and hierarchical feature matching for copy-move forgery detection[J]. Information Sciences, 2016, 345: 226-242. DOI:10.1016/j.ins.2016.01.061.
[7] Bashar M, Noda K, Ohnishi N, et al. Exploring duplicated regions in natural images[J]. IEEE Transactions on Image Processing, 2010. DOI:10.1109/tip.2010.2046599.
[8] Bayram S, Sencar H, Memon N. An efficient and robust method for detecting copy-move forgery[C]// IEEE International Conference on Acoustics, Speech and Signal Processing. Taipei, China, 2009: 1053-1056. DOI:10.1109/icassp.2009.4959768.
[9] Zandi M, Mahmoudi-Aznaveh A, Talebpour A. Iterative copy-move forgery detection based on a new interest point detector[J]. IEEE Transactions on Information Forensics and Security, 2016, 11(11): 2499-2512. DOI:10.1109/tifs.2016.2585118.
[10] Cozzolino D, Poggi G, Verdoliva L. Efficient dense-field copy-move forgery detection[J]. IEEE Transactions on Information Forensics and Security, 2015, 10(11): 2284-2297. DOI:10.1109/tifs.2015.2455334.
[11] Ryu S J, Kirchner M, Lee M J, et al. Rotation invariant localization of duplicated image regions based on Zernike moments[J]. IEEE Transactions on Information Forensics and Security, 2013, 8(8): 1355-1370. DOI:10.1109/tifs.2013.2272377.
[12] Chen B J, Coatrieux G, Wu J S, et al. Fast computation of sliding discrete Tchebichef moments and its application in duplicated regions detection[J]. IEEE Transactions on Signal Processing, 2015, 63(20): 5424-5436. DOI:10.1109/tsp.2015.2451107.
[13] Hosny K M, Hamza H M, Lashin N A. Copy-move forgery detection of duplicated objects using accurate PCET moments and morphological operators[J]. The Imaging Science Journal, 2018, 66(6): 330-345. DOI:10.1080/13682199.2018.1461345.
[14] Kang X B, Wei S M. Identifying tampered regions using singular value decomposition in digital image forensics[C]//2008 International Conference on Computer Science and Software Engineering. Wuhan, China, 2008:926-930. DOI:10.1109/csse.2008.876.
[15] Zhan L F, Zhu Y S. Passive forensics for image splicing based on PCA noise estimation[C]//2015 10th International Conference for Internet Technology and Secured Transactions(ICITST). London, UK, 2015:78-83. DOI:10.1109/icitst.2015.7412062.
[16] Namias V. The fractional order Fourier transform and its application to quantum mechanics[J]. IMA Journal of Applied Mathematics, 1980, 25(3): 241-265. DOI:10.1093/imamat/25.3.241.
[17] Xiao B, Li L P, Li Y, et al. Image analysis by fractional-order orthogonal moments[J]. Information Sciences, 2017, 382/383: 135-149. DOI:10.1016/j.ins.2016.12.011.
[18] Chen B J, Yu M, Su Q T, et al. Fractional quaternion cosine transform and its application in color image copy-move forgery detection[J].Multimedia Tools and Applications, 2019, 78(7): 8057-8073. DOI:10.1007/s11042-018-6595-z.
[19] Chen B J, Yu M, Su Q T, et al. Fractional quaternionzernike moments for robust color image copy-move forgery detection[J]. IEEE Access, 2018, 6: 56637-56646. DOI:10.1109/access.2018.2871952.
[20] Subakan Ö N, Vemuri B C. A quaternion framework for color image smoothing and segmentation[J]. International Journal of Computer Vision, 2011, 91(3): 233-250. DOI:10.1007/s11263-010-0388-9.
[21] Verdoliva L, Cozzolino D, Poggi G. A reliable order-statistics-based approximate nearest neighbor search algorithm[J]. IEEE Transactions on Image Processing, 2017, 26(1): 237-250. DOI:10.1109/tip.2016.2624141.
[22] Cozzolino D, Poggi G, Verdoliva L. Copy-move forgery detection based on PatchMatch[C]// IEEE International Conference on Image Processing. New York, USA, 2014: 5312-5316.DOI:10.1109/icip.2014.7026075.
[23] Li C, Ma Q, Xiao L M, et al. An image copy move forgery detection method using QDCT[C]//Proceedings of the International Conference on Internet Multimedia Computing and Service—ICIMCS’16. Xi’an, China, 2016:5-8. DOI:10.1145/3007669.3007689.
[24] Bravo-Solorio S, Nandi A K. Exposing duplicated regions affected by reflection, rotation and scaling[C]// IEEE International Conference on Acoustics, Speech and Signal Processing. Prague, Czech Republic, 2011: 1880-1883. DOI:10.1109/icassp.2011.5946873.
[25] Amerini I, Ballan L, Caldelli R, et al. Copy-move forgery detection and localization by means of robust clustering with J-linkage[J]. Signal Processing: Image Communication, 2013, 28(6): 659-669. DOI:10.1016/j.image.2013.03.006.

Memo

Memo:
Biography: Chen Beijing(1981—), male, doctor, associate professor, nbutimage@126.com.
Foundation items: The National Natural Science of China(No. 61572258, 61771231, 61772281, 61672294), the Priority Academic Program Development of Jiangsu Higher Education Institutions, the Qing Lan Project of Jiangsu Higher Education Institutions.
Citation: Chen Beijing, Gao Ye, Yu Ming, et al. An effective copy-move forgery detection algorithm using fractional quaternion Zernike moments and improved PatchMatch algorithm[J].Journal of Southeast University(English Edition), 2019, 35(4):431-439.DOI:10.3969/j.issn.1003-7985.2019.04.005.
Last Update: 2019-12-20