Key-Point Based Copy-Move Forgery Detection and Their Hybrid Methods: A Review

Authors

  • Harpreet Kaur Research Scholar, Department of Electronics and Communication Engineering, GZS-PTU Campus, Bathinda, Punjab, India
  • Jyoti Saxena Assistant Professor, Department of Electronics and Communication Engineering, GZS-PTU Campus, Bathinda, Punjab, India
  • Sukhjinder Singh Assistant Professor, Department of Electronics and Communication Engineering, GZS-PTU Campus, Bathinda, Punjab, India

DOI:

https://doi.org/10.53555/nneee.v2i6.189

Keywords:

Block based,, copy-move image forgery, keypoint based, SIFT, SURF and ORB

Abstract

Copy-move image forgery is one of the tampering techniques that need to be tackled with. Many copy-move forgery detection techniques such as exhaustive search, block and key-point matching based methods have been proposed for the detection of copy-move image forgery. Although key-point based methods were found better than block based methods in terms of computational efficiency, space complexity and robustness against rotation and scaling. However, key-point based methods also possess a number of limitations. So, researchers have proposed many integrated methods to cope up with the limitations of key-point based methods and to make copy move forgery detection more reliable. In this paper, keypoint based methods such as SIFT, SURF, ORB and their integrated methods are reviewed.

Author Biography

  • Sukhjinder Singh, Assistant Professor, Department of Electronics and Communication Engineering, GZS-PTU Campus, Bathinda, Punjab, India

    Assistant Professor

References

M. Sridevi, C. Mala and Siddhant Sanyam, “ Comparative Study of Image Forgery and CopyMove Techniques”, in Proc. of the Second International Conference on Computer Science Engineering and Applications (ICCSEA), vol. 166, pp. 715-723, May 2012.

Kusam, Abrol Pawanesh and Devanand “Digital Tampering Detection Techniques: A Review”, BVICAM’s International Journal of Information Technology (BIJIT), vol. 1, no. 2, pp. 125-132, Jul. – Dec. 2009.

Qureshi M. Ali and Deriche M., “A Review on Copy Move Image Forgery Detection Techniques”, 11th International Multi Conference

on Systems, Signals & Devices(SSD), pp. 1–5, Feb. 2014..

Kudke Swapnil H. and Gawande A. D., “Copy-Move Attack Forgery Detection by Using SIFT”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 2, no. 5, pp. 221-224, Apr 2013.

Christlein Vincent, Riess Christian, Jordan Johannes, Riess Corinna, and Angelopoulou Elli, “An Evaluation of Popular Copy-Move Forgery Detection Approaches”, IEEE Transactions onInformation Forensics and Security, vol. 7, no. 6, pp. 1841 – 1854, Dec, 2012.

Sekhar Resmi and A S Chithra, “Recent Blockbased Methods of Copy-Move Forgery Detection in Digital Images”, International Journal of Computer Applications, vol. 89, no. 8, pp- 28-33, Mar. 2014.

Yu Liyang, Han Qi and Niu Xiamu, “Feature Point-based Copy-Move Forgery Detection: Covering the Non-Textured Areas”, InternationalJournal of Multimedia Tools and Applications, Springer, vol. 74, issue 4, pp. 1-18, 2015.

Xunyu Pan and Siwei Lyu, “Region Duplication Detection Using Image Feature Matching”, IEEE Transactions on Information Forensics and Security, vol. 5, no. 4, pp. 857-867, Dec. 2010.

Huang Hailing, Guo Weiqiang and Zhang Yu, “Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm”, Pacific-Asia

Workshop on Computational Intelligence and Industrial Application (PACIIA), pp. 272 – 276, Dec. 2008

Ardizzone E., Bruno A. and Mazzola G., “Detecting Multiple Copies in Tampered Image”, in Proceedings of IEEE 17th International

Conference on Image Processing, pp. 2117-2120, Sep., 2010.

Amerini I., Ballan L., Caldelli R., Del Bimbo A. and Serra G., “A SIFT-Based Forensic Method for Copy–Move Attack Detection and Transformation Recovery”, IEEE Transactions on Information Forensics and Security, vol. 6, no. 3, pp. 1099 –1110, Mar. 2011.

Su Baina and Kaizhen Zhu, “Detection of Copy Forgery in Digital Images Based on LPP-SIFT”, International Conference on Industrial Control and Electronics Engineering, pp. 1773 – 1776, Aug. 2012

Jaberi Maryam, Bebis George, Hussain Muhammad and Muhammad Ghulam, “Improving the Detection and Localization of Duplicated Regions in Copy-Move Image Forgery”, 18th International Conference on Digital Signal Processing (DSP), pp. 1-6, Jul. 2013.

Li Kunlun, Li Hexin, Yang Bo, Meng Qi and Luo Shangzong, “Detection of Image Forgery Based on Improved PCA-SIFT”, in Proceedings ofComputer Engineering and Networking, vol. 277, pp 679-686, 2014.

Mohamadian. Z. and Pouvan A.A., “Detection of Duplication Forgery in Digital Images in Uniform and Non-uniform Regions”, 15th International Conference on Computer Modeling and Simulation (UKSim), pp. 455 – 460, Apr. 2013.

Hashmi Mohammad Farukh, Hambarde Aaditya R. and Keskar Avinash G., “Copy Move Forgery Detection using DWT and SIFT Features”, 13thinternational Conference on Intelligent Systems Design and Applications (ISDA), pp. 188 – 193, Dec. 2013.

Anand Vijay, Hashmi Mohammad Farukh and Keskar Avinash G., “A Copy Move Forgery Detection to Overcome Sustained Attacks Using Dyadic Wavelet Transform and SIFT Methods”, in Proceedings of Intelligent Information and Database Systems, Springer, vol. 8397, pp. 530–542, 2014.

Sudhakar K., Sandeep V.M. and Kulkarni S.,“Speeding-up SIFT based Copy Move Forgery Detection Using Level Set Approach”,

International Conference on Advances in Electronics, Computers and Communications (ICAECC), pp. 1-6, Oct. 2014.

Chihaoui Takwa, Bourouis Sami and Hamrouni Kamel, “Copy-Move Image Forgery Detection Based on SIFT Descriptors and SVD-Matching”, First International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), pp. 125-129, Mar. 2014.

Zhang Ju, Ruan Qiugi and Jin Yi, “Combined SIFT and Bi-Coherence Features to Detect Image Forgery”, 12th International Conference on Signal Processing (ICSP), pp.1859 – 1863, Oct. 2014.

Liu Lu, Ni Rongrong, Zhao Yao and Li Siran, “Improved SIFT-based Copy-move Detection Using BFSN Clustering and CFA Features”,

Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 626 – 629, Aug. 2014.

Bo Xu, Junwen Wang, Guangjie Liu and Yuewei Dai, “Image Copy-move Forgery Detection Based on SURF”, International Conference on Multimedia Information Networking and Security(MINES), pp. 889 – 892, Nov. 2010.

Lin Shinfeng D. and Wu Tszan, “An Integrated Technique for Splicing and Copy-move Forgery Image Detection”, 4th International Conference on Image and Signal Processing (CISP), vol. 2, pp. 1086 – 1090, Oct. 2011.

Zhang Guang-qun and Wang Hang-jun, “SURF-based Detection of Copy-Move Forgery in Flat Region”, International Journal of Advancements in Computing Technology (IJACT), vol. 4, no. 17, Sep., 2012.

Mishra Parul, Mishra Nishchol, Sharma Sanjeev and Patel Ravindra, “Region Duplication Forgery Detection Technique Based on SURF and HAC”, The Scientific World Journal, 8 pages, 2013.

Hashmi M.F., Anand V., Keskar A.G., “A Copy-move Image Forgery Detection Based on Speeded up Robust Feature Transform and Wavelet Transforms”, International Conference on Computer and Communication Technology (ICCCT), pp. 147 – 152, Sep. 2014.

Jiming Zheng and Liping Chang, “Detection of Region-duplication Forgery in Image Based on Key Points' Binary Descriptors”, Journal of Information & Computational Science, vol. 11, no. 11, pp. 3959-3966, Jul, 2014.

Zhu Ye, Shen Xuanjing and Chen Haipeng, “Copy-Move Forgery Detection Based on Scaled ORB”, Proceedings of Multimedia Tools

and Applications, vol. 75, no. 9, pp. 1-13, Jan.2015.

Downloads

Published

2015-06-30

How to Cite

Kaur, H., Saxena, J., & Singh, S. (2015). Key-Point Based Copy-Move Forgery Detection and Their Hybrid Methods: A Review. Journal of Advance Research in Electrical & Electronics Engineering (ISSN 2208-2395), 2(6), 06-13. https://doi.org/10.53555/nneee.v2i6.189