Abstract Most of the images today are stored in digital format. With the advent of digital imagery, tampering of images became easy. The problem has become altogether intensified due to the availability of image tampering softwares. Moreover there exist cameras with different resolutions and encoding techniques. Detecting forgery in such cases becomes a challenging task. Furthermore, the forged image may be compressed or resized which further complicates the problem. This article focuses on blind detection of copy-move forgery using a combination of an invariant feature transform and a wavelet transform. The feature transform employed is Speeded Up Robust Features (SURF) and the wavelet transforms employed are Discrete Wavelet Transform (DWT) and Dyadic Wavelet Transform (DyWT). A comparison between the performances of the two wavelet transforms is presented. The proposed algorithms are different from the previously proposed methods in a way that they are applied on the whole image, rather than after dividing the image in to blocks. A comparative study between the proposed algorithm and the previous block-based methods is presented. From the results obtained, we conclude that these algorithms perform better than their counterparts in terms of accuracy, computational complexity and robustness to various attacks.

References

[1] 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, 2011.

[2] Bay H., Tuytelaars T., and Van Gool L., “Surf: Speeded up Robust Features,” in Proceedings of European Conference on Computer Vision, Graz, pp. 404-417, 2006.

[3] Bayram S., Sencar H., and Memon N., “An Efficient and Robust Method for Detecting Copy-Move Forgery,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, pp. 1053-1056, 2009.

[4] Bo X., Junwen W., Guangjie L., and Yuewei D., “Image Copy-Move Forgery Detection Based on SURF,” in Proceedings of IEEE International Conference on Multimedia Information Networking and Security, Nanjing, pp. 889-892, 2010.

[5] Cao Y., Gao T., Fan L., and Yang Q., “A Robust Detection Algorithm for Copy-Move Forgery in Digital Images,” Forensic Science International, vol. 214, no. 1, pp. 33-43, 2012.

[6] Fridrich J., Soukal D., and Lukáš J., “Detection of Copy-Move Forgery in Digital Images,” in Proceedings of Digital Forensic Research Workshop, Cleveland, pp. 1-8, 2003.

[7] Haar A., “Zur Theorie Der Orthogonalen Funktionensysteme,” Mathematische Annalen, vol. 69, no. 3, pp. 331-371, 1910.

[8] Huang H., Guo W., and Zhang Y., “Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm,” in Proceedings of IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, Wuhan, pp. 272-276, 2008.

[9] Hsu H. and Wang M., “Detection of Copy-Move Forgery Image Using Gabor Descriptor,” in Proceedings of IEEE International Conference on Anti-Counterfeiting, Security and Identification, Taipei, pp. 1-4, 2012.

[10] Juan L. and Gwun O., “A Comparison of Sift, PCA-SIFT and SURF,” International Journal of Image Processing, vol. 3, no. 4, pp. 143-152, 2009.

[11] Khalifa O., “Wavelet Coding Design for Image Data Compression,” The International Arab Journal of Information Technology, vol. 2, no. 2, pp. 118-127, 2005.

[12] Li G., Wu Q., Tu D., and Sun S., “A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries Based on DWT and SVD,” in Proceedings of IEEE International Conference on Multimedia and Expo, Beijing, pp. 1750-1753, 2007.

[13] Li L., Li S., Zhu H., Chu S., Roddick J., and Pan J., “An Efficient Scheme for Detecting Copy- Move Forged Images by Local Binary Patterns,” Journal of Information Hiding and Multimedia Signal Processing, vol. 4, no. 1, pp. 46-56, 2013.

[14] Liu T., Kim S., Lim S., and Lee H., “Selection of Distinctive Sift Feature Based on Its Distribution on Feature Space and Local Classifier for Face Recognition,” The International Arab Journal of Fast and Robust Copy-Move Forgery Detection Using Wavelet Transforms and SURF 311 Information Technology, vol. 10, no. 1, pp. 95- 101, 2013.

[15] Mallat S. and Zhong S., “Characterization of Signals from Multiscale Edges,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 7, pp. 710-732, 1992.

[16] Mishra P., Mishra N., Sharma S., and Patel R., “Region Duplication Forgery Detection Technique Based on SURF and HAC,” The Scientific World Journal, vol. 2013, no. 6, pp. 8, 2013.

[17] Muhammad G., Hussain M., and Bebis G., “Passive Copy Move Image Forgery Detection Using Undecimated Dyadic Wavelet Transform,” Digital Investigation, vol. 9, no. 1, pp. 49-57, 2012.

[18] Popescu A. and Farid H., “Exposing Digital Forgeries By Detecting Duplicated Image Regions,” Technical Report TR2004-515, Dartmouth College, 2004.

[19] Qiao M., Sung A., Liu Q., and Ribeiro B., “A Novel Approach for Detection of Copy-Move Forgery,” in Proceedings of 5th International Conference on Advanced Engineering Computing and Applications in Sciences, Lisbon, pp. 44-47, 2011.

[20] Ryu S., Lee M., and Lee H., “Detection of Copy- Rotate-Move Forgery Using Zernike Moments,” in Proceedings of International Workshop on Information Hiding, Calgary, pp. 51-65, 2010.

[21] Zhao J. and Guo J., “Passive Forensics for Copy- Move Image Forgery Using A Method Based on DCT and SVD,” Forensic Science International, vol. 233, no. 1, pp.158-166, 2013. Mohammad Hashmi the author completed his B.E. from VNIT, Nagpur in 1979 and received gold medal for the same. He completed his M.E. from IISc, Bangalore in1983, receiving the gold medal again. He also completed his Ph.D. from VNIT Nagpur in1997.The author is a member of IAENG. He has 26 years of teaching experience and 7 years of industrial experience. He is currently a Professor at Department of Electronics Engineering, VNIT Nagpur. His current research interests include Computer Vision, Soft Computing, and Fuzzy Logic etc. Dr.Keskar is a senior member of IEEE, FIETE, LMISTE, FIE. Avinash Keskar the author received his B.E in Electronics & Communication Engineering from R.G.P.V Bhopal University in 2007. He obtained his M.E. in Digital Techniques & Instrumentation in 2010 from R.G.P.V Bhopal University. He received Ph.D. at VNIT Nagpur under the supervision of Dr.A.G.Keskar. He has published up to 50 papers in National/International Conferences/ Journals. He has a teaching experience of 7 years. He is currently an Assistant professor at Department of Electronics and Communication Engineering, National Institute of Technology, Warangal. His current research interests are Image Processing, Internet of Things, Embedded Systems, Biomedical Signal Processing, Computer Vision, Circuit Design, and Digital IC Design etc. Mr. Mohammad F. Hashmi is a member of IEEE, ISTE, and IAENG.