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Reseach Article

Image Forgery and Detection of Copy Move Forgery in Digital Images: A Survey of Recent Forgery Detection Techniques

by Ramandeep Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 139 - Number 5
Year of Publication: 2016
Authors: Ramandeep Kaur
10.5120/ijca2016909164

Ramandeep Kaur . Image Forgery and Detection of Copy Move Forgery in Digital Images: A Survey of Recent Forgery Detection Techniques. International Journal of Computer Applications. 139, 5 ( April 2016), 39-47. DOI=10.5120/ijca2016909164

@article{ 10.5120/ijca2016909164,
author = { Ramandeep Kaur },
title = { Image Forgery and Detection of Copy Move Forgery in Digital Images: A Survey of Recent Forgery Detection Techniques },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 139 },
number = { 5 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 39-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume139/number5/24490-2016909164/ },
doi = { 10.5120/ijca2016909164 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:40:41.303409+05:30
%A Ramandeep Kaur
%T Image Forgery and Detection of Copy Move Forgery in Digital Images: A Survey of Recent Forgery Detection Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 139
%N 5
%P 39-47
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the development of Image processing editing tools and software, an image is manipulated very easily. The image manipulation detection is essential for the reason that an image can be employed as legal evidence, in the field of forensics investigations, and also in numerous various other fields. The image forgery detection based on pixels aims to validate the digital image authenticity with no aforementioned information of the main image. There are several means intended for tampering a digital image, for example, copy-move or splicing, resampling a digital image (stretch, rotate, resize), removal as well as the addition of an object from your image. Copy move image forgery detection is utilized to figure out the replicated regions as well as the pasted parts, however forgery detection may possibly vary dependant on whether or not there is virtually any post-processing on the replicated part before inserting the item completely to another party. Typically, counterfeiters utilize many operations like rotation, filtering, JPEG compression, resizing as well as the addition of noise to the main image before pasting, that make this thing challenging to recognize the copy move image forgery. Hence, forgery detector needs to be robust to any or all manipulations and also the latest editing software tools. In the literature part, various researchers portrayed the working scenario of copy-move image forgery utilizing the similarity measures as well as the relationship among the original parts of the image and their pasted parts in the similar image. This research paper illustrates recent issues in the techniques of forgery detection and also all their comparative analysis.

References
  1. Pan, X. Z., and Wang, H. M. “The Detection Method of Image Regional Forgery Based DWT and 2DIMPCA”, Advanced Materials Research, 2012, Vol. 532, pp. 692-696.
  2. Shivakumar, B., and Baboo, S. S. “Automated Forensic Method for Copy-Move Forgery Detection based on Harris Interest Points and SIFT Descriptors”, International Journal of Computer Applications, 2011, Vol. 27, No. 3.
  3. Yao, H., Tang, Z., Qiao, T., Zhao, Y., and Mao, H. “Detecting Copy-Move Forgery Using Non-negative Matrix Factorization” , proceedings of Third International Conference on Multimedia Information Networking and Security (MINES), 2011.
  4. Pujari, V. S., and Sohani, M. “A Comparative Analysis On Copy Move Forgery Detection Using Frequency Domain Techniques”, International Journal of Global Technology Initiatives, 2012, Vol.1, No. 1, pp. E104-E111.
  5. Chen, L., Ni, J., Lu, W., Sun, W., and Huang, J. “Region duplication detection based on Harris corner points and step sector statistics”, Journal of Visual Communication and Image Representation, 2013, Vol. 24, No. 3, pp. 244-254.
  6. Liu, M.-H., and Xu, W.-H. “Detection of copy-move forgery image based on fractal and statistics”, Journal of Computer Applications, 2011, Vol. 8.
  7. Yadav, P., Rathore, Y., and Yadu, A. “DWT Based Copy-Move Image Forgery Detection”, International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE), 2012, Vol. 1, No.5, pp. 56-58.
  8. Pujari, V. S., and Sohani, M. “A Comparative Analysis on Copy Move Forgery Detection in Spatial Domain Method Using Lexicographic and Non Lexicographic techniques”, IJECCE, 2012, Vol. 3, No. 1, pp. 136-139.
  9. Shivakumar, B., and Santhosh Baboo, L. D. S. “Detecting copy-move forgery in digital images: a survey and analysis of current methods”, Global Journal of Computer Science and Technology, 2010, Vol. 10, No. 7.
  10. Chen, L., Lu, W., and Ni, J. “An Image Region Description Method Based on Step Sector Statistics and its Application in Image Copy-Rotate/Flip-Move Forgery Detection”, International Journal of Digital Crime and Forensics (IJDCF), 2012, Vol. 4, No. 1, pp. 49-62.
  11. Liu, G., Wang, J., Lian, S., & Wang, Z. “A passive image authentication scheme for detecting region duplication forgery with rotation”, Journal of Network and Computer Applications, 2011, Vol. 34, No. 5, pp. 1557-1565.
  12. Sridevi, M., Mala, C., & Sanyam, S. “Comparative Study of Image Forgery and Copy-Move Techniques”, Springer: Advances in Computer Science, Engineering & Applications, 2012, pp. 715-723.
  13. A merini, I., Barni, M., Caldelli, R., & Costanzo, A., “Counter-forensics of SIFT-based copy-move detection by means of keypoint classification”, EURASIP Journal on Image and Video Processing, 2013, Vol. 18, No.1.
  14. Muhammad, G., Khawaji, K., Hussain, M., and Bebis, G. “Blind copy move image forgery detection using dyadic undecimated wavelet transform”, Digital Signal Processing, 2011.
  15. Piva, A. “An Overview on Image Forensics”, ISRN Signal Processing, 2013.
  16. Wang, J.-W., Zhang, Z., Liu, G.-J., Dai, Y., and Wang, Z. “Fast and robust forensics for image region duplication forgery”, Acta Automatica Sinica, 2009, Vol. 35, No.12, pp. 1488- 1495.
  17. Mahdian, B., and Saic, S. “A bibliography on blind methods for identifying image forgery”, Signal Processing: Image Communication, 2010, Vol. 25, No. 6, pp. 389-399.
  18. Math, S., and Tripathi, R. “Digital Forgeries: Problems and Challenges”, International Journal of Computer Applications, 2010, Vol. 5, No. 12.
  19. Hwang, M. G., and Har, D. H. “A Novel Forged Image Detection Method Using the Characteristics of Interpolation”, Journal of Forensic Sciences, 2013, Vol. 58, No.1, pp. 151-162.
  20. Taktak, W., and Dugelay, J.-L. “Digital Image Forensics: A Two-Step Approach for Identifying Source and Detecting Forgeries”, The Era of Interactive Media, 2013, pp. 37-51.
  21. Jian-feng, Z. G.-j. Z. “The Application of Electronic Signature Technology in Online Bidding System”, Journal of Changzhou Vocational College of Information Technology, 2011, Vol. 4, No. 7.
  22. Chang, I.-C., and Hsieh, C.-J “Image Forgery Using An Enhanced Bayesian Matting Algorithm”, Intelligent Automation & Soft Computing, 2011, Vol. 17, No. 2, pp. 269-281.
  23. Lin, H.-J., Wang, C.-W., and Kao, Y.-T. “Fast copy-move forgery detection”, WSEAS Transactions on Signal Processing, 2009, Vol. 5, No. 5, pp. 188-197.
  24. Peng, F., Nie, Y.-y., and Long, M. “A complete passive blind image copy-move forensics scheme based on compound statistics features”, Forensic Science International, 2011, Vol. 212, No. 1, pp. e21-e25.
  25. Barnes, C., Goldman, D. B., Shechtman, E., and Finkelstein, A. “The generalized patchmatch correspondence algorithm”, Computer Vision–ECCV 2010, Springer, 2010, pp. 29-43.
  26. Ghosh, P., Gelasca, E. D., Ramakrishnan, K., and Manjunath, B. “Duplicate image detection in large scale databases”, Advances in Intelligent Information Processing: Tools and Applications, 2007, pp. 149-166.
  27. Christlein, V., Riess, C., and Angelopoulou, E. “On rotation invariance in copy-move forgery detection”, IEEE International Workshop on Information Forensics and Security (WIFS), 2010.
  28. Mahdian, B., and Saic, S. “Detection of copy– move forgery using a method based on blur moment invariants”, Forensic Science International, 2007, Vol. 171, No. 2, pp. 180-189.
  29. Mohamadian, Z., and Pouyan, A. A. “Detection of Duplication Forgery in Digital Images in Uniform and Non-uniform Regions”, UKSim, 2013.
  30. Popescu, A. C., and Farid, H. “Exposing digital forgeries by detecting duplicated image regions” Dept. of Comput. Sci., Dartmouth College, Tech. Rep. TR 2004-515, 2004.
  31. Ting, Z., and Rang-ding, W. “Copy-move forgery detection based on SVD in digital image”, 2nd International conference on Image and Signal Processing, 2009.
  32. Bashar, M., Noda, K., Ohnishi, N., and Mori, K. “Exploring duplicated regions in natural images”, IEEE Transactions on Image Processing, 2010, Vol. 99, No. 1.
  33. Zimba, M., & Xingming, S. “DWT- PCA(EVD) Based Copy-move Image Forgery Detection”, International Journal of Digital Content Technology and its Applications, 2011, Vol. 5, No. 1.
  34. Luo, W., Huang, J., and Qiu, G. “Robust detection of region-duplication forgery in digital image”, 18th International Conference on Pattern Recognition, ICPR 2006, 2006.
  35. Bravo-Solorio, S., and Nandi, A. K. “Automated detection and localisation of duplicated regions affected by reflection, rotation and scaling in image forensics”, Signal Processing, 2011, Vol. 91, No. 8, pp. 1759-1770.
  36. Wang, J., Liu, G., Li, H., Dai, Y., and Wang, Z. “Detection of image region duplication forgery using model with circle block”, International Conference on Multimedia Information Networking and Security, MINES'09, 2009.
  37. Sridevi, M., Mala, C., and Sandeep, S. “Copy– move image forgery detection”, Computer Science & Information Technology (CS & IT), 2012, Vol. 52, pp. 19-29.
  38. Fridrich, A. J., Soukal, B. D., and Lukáš, A. J. “Detection of copy-move forgery in digital images”, Digital Forensic Research Workshop, 2003.
  39. Zhang, J., Feng, Z., and Su, Y. “A new approach for detecting copy-move forgery in digital images”, 11th IEEE Singapore International Conference on Communication Systems, 2008.
  40. Bayram, S., Sencar, H. T., and Memon, N. “An efficient and robust method for detecting copy-move forgery”, IEEE International Conference on Acoustics, Speech and Signal Processing, 2009.
  41. Li, L., Li, S., and Wang, J. “Copy-move forgery detection based on PHT”, World Congress on Information and Communication Technologies, 2012.
  42. Ghorbani, M., Firouzmand, M., and Faraahi, A. “DWT-DCT (QCD) based copy-move image forgery detection”, 18th International Conference on Systems, Signals and Image Processing, 2011.
  43. Li, L., Li, S., Zhu, H., Chu, S.-C., Roddick, J. F., and Pan, J.-S. “An Efficient Scheme for Detecting Copymove Forged Images by Local Binary Patterns”, Journal of Information Hiding and Multimedia Signal Processing, 2013, Vol. 4, No. 1, pp. 46-56.
  44. Qiao, M., Sung, A., Liu, Q., and Ribeiro, B. “A novel approach for detection of copy-move forgery”, Fifth International Conference on Advanced Engineering Computing and Applications in Sciences, 2011.
  45. Huang, H., Guo, W., and Zhang, Y. “Detection of copy-move forgery in digital images using SIFT algorithm”, Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 2008.
  46. Bo, X., Junwen, W., Guangjie, L., and Yuewei, D. “Image copy-move forgery detection based on SURF”, International Conference on Multimedia Information Networking and Security, 2010.
  47. Zheng, J., Haoa, W., and Zhub, W. “Detection of Copy-move Forgery Based on Keypoints’ Positional Relationship”, Journal of Information and Computational Science, 2012, Vol. 1, No. 3, pp. 53-60.
Index Terms

Computer Science
Information Sciences

Keywords

Image Forgery Copy-Move Image forgery Image Forgery Detection Tampering Digital Forensics Duplication forgery Detection