Performance Analysis of Copy-Move Forgery Detection Techniques

Gulivindala Suresh *, Chanamallu Srinivasa Rao **
*_**Department of Electronics & Communication Engineering, JNTUK University College of Engineering, Kakinada, Andhra pradesh, India.
Periodicity:January - March'2019
DOI : https://doi.org/10.26634/jip.6.1.15925

Abstract

Copy Move Forgery (CMF) is a manipulation process, where a part of the image is copied and moved to another region in the same image. The advanced growth in technology and photo-editing software lead to the malicious manipulation of images. Distribution of such tampered images through high speed digital networks and social media is also increased, which leads to the incredibility of the images and the underlying information. Hence, it is much demanded to develop, evaluate, and propose CMF detection techniques. CMF detection can be achieved either by keypoint approach or block-based approach. In this paper, performance of block-based and keypoint based CMF detection and localization techniques are analyzed.

Keywords

Copy Move Forgery, Block-Based, Keypoint Based, Forgery Detection.

How to Cite this Article?

Suresh, G., & Rao, C. S. (2019). Performance Analysis of Copy-Move Forgery Detection Techniques. i-manager's Journal on Image Processing, 6(1), 38-43. https://doi.org/10.26634/jip.6.1.15925

References

[1]. Amerini, I., Ballan, L., Caldelli, R., Del Bimbo, A., & Serra, G. (2011). A SIFT- based forensic method for copymove attack detection and transformation recovery. IEEE Transactions on Information Forensics and Security, 6(3), 1099-1110. https://doi.org/10.1109/TIFS.2011.2129512
[2]. Amerini, I., Ballan, L., Caldelli, R., Del, A., Del, L., & Serra, G. (2013). Copy-Move forgery detection and localization by means of Robust Clustering with J-Linkage. Signal Processing: Image Communication, 28(6), 659- 669.
[3]. Bashar, M. K., Noda, K., Ohnishi, N., & Mori, K. (2010). Exploring duplicated regions in natural images. IEEE Transactions on Image Processing, 99, 1-40.
[4]. Cao, Y., Gao, T., Fan, L., & Yang, Q. (2012). A robust detection algorithm for copy-move forgery in digital images. Forensic Science International, 214(1–3), 33-43. https://doi.org/10.1016/j.forsciint.2011.07.015
[5]. CASIA Tampered Image Detection Evaluation Database. (2010). https://doi.org/10.4018/978-1-5225- 0983- 7.ch074
[6]. Emam, M., Han, Q., & Zhang, H. (2018). Two-stage Keypoint detection scheme for region duplication forgery detection in digital images. Journal of Forensic Sciences, 63 (1), 102-111. https://doi.org/10.1111/1556-4029.13456
[7]. Farid, H. (2009). Image Forgery Detection. IEEE Signal Processing Magazine, 26(2), 16-25. doi:10.1109/ MSP.2008.931079
[8]. Gan, A., & Zhong, J. (2014). Image copy-move forgery blind detection algorithm based on the normalized histogram multi-feature vectors. Journal of Software Engineering, 9(2), 254-264. https://doi.org/ 10.1017/CBO9781107415324. 004
[9]. Hashmi, M. F., Hambarde, A. R., & Keskar, A. G. (2014). Robust Image Authentication Based on HMM and SVM Classifiers. Engineering Letters, 22(4).
[10]. Huang, Y., Lu, W., Sun, W., & Long, D. (2011). Improved DCT-based detection of copy-move forgery in images. Forensic Science International, 206(1–3), 178- 184. https://doi.org/10.1016/j.forsciint.2010.08.001
[11]. Huang, H., Guo, W., & Zhang, Y. (2008). Detection of Copy-Move forgery in digital images using SIFT Algorithm. In 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application (Vol. 2, pp.272- 276). https://doi.org/10.1109/PACIIA.2008.240
[12]. Isaac, M. M., & Wilscy, M. (2015). Image forgery detection based on Gabor Wavelets and Local Phase Quantization. In Procedia Computer Science, 58,76-83. https://doi.org/10.1016/j.procs.2015.08.016
[13]. Jaberi, M., Bebis, G., Hussain, M., & Muhammad, G. (2014). Accurate and robust localization of duplicated region in copy- move image forgery. Machine Vision and Applications, 25(2), 451-475. https://doi.org/10.1007/ s00138-013-0522-0
[14]. Jing, L., & Shao, C. (2012). Image copy- move forgery detecting based on local invariant feature. Journal of Multimedia, 7(1), 90-97. https://doi.org/ 10.4304/jmm.7.1.90-97
[15]. Kaur, A., & Richa, S. (2013). Copy-Move Forgery Detection using DCT and SIFT. International Journal of Computer Applications, 70(7), 30-34.
[16]. Kumar, S., Desai, J. V., & Mukherjee, S. (2015). Copy Move Forgery detection in Contrast Variant Environment using Binary DCT Vectors. International Journal of Image, Graphics & Signal Processing, 7(6), 38-44. https://doi.org/ 10.5815/ijigsp.2015.06.05
[17]. Kuznetsov, A., & Myasnikov, V. (2017). A new copymove forgery detection algorithm using image preprocessing procedure. Proceedia Engineering, 201, 436-444. https://doi.org/.1037//0033-2909.I26.1.78
[18]. Lee, J. C. (2015). Copy-move image forgery detection based on Gabor magnitude. Journal of Visual Communication and Image Representation, 31, 320-334. https://doi.org/10.1016/j.jvcir.2015.07.007
[19]. Li, J., Li, X., Yang, B., & Sun, X. (2015). Segmentationbased image copy-move forgery detection scheme. IEEE Transactions on Information Forensics and Security, 10(3), 507-518. https://doi.org/10.1109/TIFS.2014. 2381872
[20]. Li, L., Li, S., Zhu, H., Chu, S. C., Roddick, J. F., & Pan, J. S. (2013). An efficient scheme for detecting copy-move forged images by local binary patterns. Journal of Information Hiding and Multimedia Signal Processing, 4(1), 46-56.
[21]. Lin, Z., He, J., Tang, X., & Tang, C. K. (2009). Fast , automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis. Pattern Recognition, 42(11), 2492-2501. https://doi.org/10.1016/ j.patcog.2009.03.019
[22]. Lin, G., Chang, M. K., & Chen, Y. L. (2011). A Passive- Blind Forgery Detection Scheme based on Content. Adaptive Quantization Table Estimation, 21(4), 421–434.
[23]. Liu, G., Wang, J., Lian, S., & Wang, Z. (2011). A passive image authentication scheme for detecting region-duplication forgery with rotation. Journal of Network and Computer Applications, 34(5), 1557-1565. https://doi.org/10.1016/j.jnca.2010.09.001
[24]. Mahmood, T., Nawaz, T., Irtaza, A., Ashraf, R., Shah, M., & Mahmood, M. T. (2016). Copy-Move Forgery Detection technique for Forensic Analysis in Digital Images. Mathematical Problems in Engineering, 2016, Article ID 8713202. https://doi.org/10.1155/2016/8713202
[25]. Meng, X. Z., Niu, S. Z., & Zou, J. C. (2010, October). Tamper detection for shifted double jpeg compression. In 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (pp. 434- 437). IEEE. https://doi.org/10.1109/ IIHMSP.2010.111
[26]. Mishra, P., Mishra, N., Sharma, S., & Patel, R. (2013). Region Duplication Forgery Detection technique based on SURF and HAC. The Scientific World Journal, 2013, 1-8.
[27]. Muhammad, G., Hussain, M., & Bebis, G. (2012). Passive copy move image forgery detection using undecimated dyadic wavelet transform. Digital Investigation, 9(1), 49-57. https://doi.org/10.1016/ j.diin.2012.04.004
[28]. Pan, X., & Lyu, S. (2010a). Region Duplication Detection using Image Feature Matching. IEEE Transactions on Information Forensics and Security, 5(4), 857-867.
[29]. Pan, X., & Lyu, S. (2010b). Detecting image region duplication using SIFT features. In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (pp.706-1709). https://doi.org/10.1109/ICASSP.2010. 549548 2
[30]. Peng, F., Nie, Y. Y., & Long, M. (2011). A complete passive blind image copy-move forensics scheme based on compound statistics features. Forensic Science International, 212(1-3), e21-e25. https://doi.org/10.1016/ j.forsciint.2011.06.011
[31]. Redi, J. A., Taktak, W., & Dugelay, J. L. (2011). Digital Image Forensics: A booklet for Beginners. Multimedia Tools and Applications, 51(1), 133-162.
[32]. Ryu, S. J., Kirchner, M., Lee, M. J., & Lee, H. K. (2013). Rotation invariant localization of duplicated image regions based on zernike moments. IEEE Transactions on Information Forensics and Security, 8(8), 1355-1370. https://doi.org/10.1109/TIFS.2013.2272377
[33]. Tralic, D., Zupancic, I., Grgic, S., & Grgic, M. (2013). CoMoFoD - New Database for Copy-Move Forgery Detection. Proceedings of 55th International Symposium ELMAR- 2013, (pp.49-54).
[34]. Wang, C., Zhang, Z., & Zhou, X. (2018). An Image Copy-Move Forgery Detection Scheme based on A-KAZE and SURF Features. Symmetry, 10 (12), 706. https://doi.org/10.3390/sym10120706
[35]. Wang, H., & Wang, H. (2018). Perceptual Hashing- Based Image Copy-Move Forgery Detection. Security and Communication Networks, 2018, 1-11.
[36]. Warif, N. B. A., Wahab, A. W. A., Idris, M. Y. I., Ramli, R., Salleh, R., Shamshirband, S., & Choo, K. K. R. (2016). Copy-move forgery detection: Survey, challenges and future directions. Journal of Network and Computer Applications, 75, 259-278. https://doi.org/10.1016/ j.jnca.2016.09.008
[37]. Yang, B., Sun, X., Chen, X., Zhang, J., & Li, X. (2013). An efficient forensic method for copy-move forgery detection based on DWT- FWHT. Radioengineering, 22(4), 1098-1105.
[38]. Yang, B., Sun, X., Guo, H., Xia, Z., & Chen, X. (2018). A copy-move forgery detection method based on CMFDSIFT. Multimedia Tools and Applications, 77(1), 837-855. https://doi.org/10.1007/s11042-016-4289-y
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