Accurate and robust localization of duplicated region in copy-move image forgery

Machine Vision and Applications

Volumn 25, Issue 2, 2014, Pages 451-475

  Jaberi, Maryam ^a   Bebis, George ^a   Hussain, Muhammad ^b   Muhammad, Ghulam ^c  

^a University of Nevada   (United States)

^b KING SAUD UNIVERSITY   (Saudi Arabia)

^c KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

Blind image forensics; Copy move image forgery; Matching; MIFT; SIFT

Indexed keywords

EID: 84894902017     PISSN: 09328092     EISSN: 14321769     Source Type: Journal    
DOI: 10.1007/s00138-013-0522-0     Document Type: Article

References (40)

1. Luo, W.; Huang, J.; Qiu, G.: Robust detection of region-duplication forgery in digital images. In: Proceedings of International Conference on Pattern Recognition, pp. 746-749. Washington, D.C. (2006)
2. Farid, H.: A survey of image forgery detection. IEEE Signal Process. Mag. 2(26), 16-25 (2009)
3. Zhang, J.; Feng, Z.; Su, Y.: A new approach for detecting copy-move forgery in digital images. In: IEEE Singapore International Conference on Communication Systems, pp. 362-366. (2008)
4. Fridrich, J.; Soukal, D.; Lukas, J.: Detection of Copy-Move Forgery in Digital Images. Department of Electrical and Computer Engineering, Department of Computer Science SUNY Binghamton, Binghamton, NY (2003)
5. Popescu, A.C.; Farid, H.: Exposing digital forgeries by detecting duplicated image regions. In: Technical Report TR2004-515, Dartmouth College, August (2004)
6. Lin, Z.; Wang, R.; Tang, X.; Shum, H.-V.: Detecting doctored images using camera response normality and consistency. In: Proceedings of Computer Vision and Pattern Recognition. San Diego, CA, (2005)
7. Mahdian, B.; Saic, S.: Detection of copy move forgery using a method based on blur moment invariants. Forensic Sci. Int. 171, 180-189 (2007)
8. Li, G.; Wu, Q.; Tu, D.; Sun, S.: A sorted neighborhood approach for detecting duplicated regions in image forgeries based on DWT and SVD. In: IEEE International Conference on Multimedia and Expo, pp. 1750-1753. Beijing, China (2007)
9. Khan, S.; Kulkarni, A.: An efficient method for detection of copy-move forgery using discrete wavelet transform. Int. J. Comput. Sci. Eng. (IJCSE) 2(5), 1801-1806 (2010)
10. Muhammad, G.; Hussain, M.; Khawaji, K.; Bebis, G.: Blind copy move image forgery detection using dyadic uncedimated wavelet transfor. In: 17th International Conference on Digital Signal Processing. Corfu, Greece, July (2011)
11. Huang, H.; Guo, W.; Zhang, Y.: Detection of copy-move forgery in digital images using SIFT algorithm. In: IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application (2008)
12. Pan, X.; Lyu, S.: Region duplication detection using image feature matching. IEEE Trans. Inf. Forensics Secur. 5(4), 857-867 (2010)
13. Amerini, I.; Ballan, L.; Caldelli, R.; Del Bimbo, A.; Serra, G.: A SIFT-based forensic method for copy-move attack detection and transformation recovery. IEEE Trans. Inf. Forensics Secur. 6(3), 1099-1110 (Jun. 2011)
14. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2), 91-110 (2004)
15. Mikolajczyk, K.; Schmid, C.: Indexing based on scale invariant interest points. In: Proceedings of Eighth International Conference on Computer Vision, pp. 525-531. (2001)
16. Mikolajczyk, K.; Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615-1630 (2005)
17. Chen, J.; Shan, S.; He, C.; Zhao, G.; Pietikainen, M.; Chen, X.; Gao, W.: WLD: a robust local image descriptor. IEEE Trans. Pattern Anal. Mach. Intell 32, 1705-1720 (2010)
18. Moreels, P.; Perona, P.: Evaluation of features detectors and descriptors based on 3D objects. Int. J. Comput. Vis. 73(3), 800-807 (2007)
19. Dalal, N.; Triggs, B.: Histograms of oriented gradients for human detection. In: Computer Vision and Pattern Recognition. San Diego, CA, June 20-25 (2005)
20. Guo, X.; Cao, X.; Zhang, J.; Li, X.: Mift: A mirror reflection invariant feature descriptor. In: Proceedings of ACCV (2009)
21. Ojala, T.; PietikaÈinen, M.; Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recognit. 29, 51-59 (1996)
22. Chung, Y.C.; Tony, H.X.; He, Z.: Building recognition using sketch-based representations and spectral graph matching. In: IEEE International Conference on Computer Vision (ICCV 2009), Kyoto
23. Ke, Y.; Sukthankar, R.: PCA-SIFT: A More Distinctive Representation for Local Image Descriptors. CVPR, Washington, DC (2004)
24. Mahdian, B.; Siac, S.: A bibliography on blind methods for identifying image forgery. In: Signal Processing: Image Communication, pp. 389-399. (2010)
25. Kumar, S.; Das, P.K.: Copy-move forgery detection in digital images: progress and challenges. Int. J. Comput. Sci. Eng. 3(2), 652-663 (February 2011)
26. Fischler, M.A.; Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24, 381-395 (1981)
27. Raguram, R.; Frahm, M.; Pollefeys, M.: A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus. In: ECCV 2008, Part II, LNCS, vol. 5305, pp. 500-503. Springer, Heidelberg (2008)
28. Provost, F.; Fawcett, T.; Kohavi, R.: The case against accuracy estimation for comparing induction algorithms. In: Proceeding of the 15th International Conference on Machine Learning, pp. 445-453. Morgan Kaufmann, San Francisco (1998)
29. CASIA Image Tampering Detection Evaluation Database, ver. 2.0. http://forensics.idealtest.org. (2010)
30. Granty, R.; Aditya, T.; Madhu, S.: Survey on passive methods of image tampering detection. In: 2010 International Conference on Communication and Computational Intelligence (INCOCCI), Dec.; pp. 431-436. (2010)
31. Vedaldi, A.; Fulkerson, B.: An Open and Portable Library of Computer Vision Algorithms. http://www.vlfeat.org/. (2008)
32. Beis, J.; Lowe, D.G.: Shape indexing using approximate nearest-neighbor search in high-dimensional spaces. In: Conference on Computer Vision and Pattern Recognition, Puerto Rico, pp. 1000-1006. (1997)
33. Ojala, T.; Pietikainen, M.; Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971-987 (2002)
34. Huang, D.; Shan, C.; Ardabilian, M.; Wang, Y.; Chen, L.: Local binary patterns and its application to facial image analysis: a survey. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 41(6), 765-781 (2011)
35. Lazebnik, S.; Schmid, C.; Ponce, J.: A sparse texture representation using local affine regions. In: Technical Report CVR-TR-2004-01, Beckman Institute, University of Illinois (2004)
36. Bay, H.; Tuytelaars, T.; Van Gool, L.: SURF: speeded up robust features. In: European Computer Vision Conference (ECCV) (2006)
37. Canny, J.: A computational approach to edge detection. IEEE Trans Pattern Anal. Mach. Intell. 8(6), 679-698 (1986)
38. Powers, D.M.W.: Evaluation: from precision, recall and f-factor to roc, informedness, markedness & correlation. J. Mach. Learn. Technol. 2(1), 37-63 (2011)
39. Muhammad, G.; Hussain, M.; Bebis, G.: Passive copy move image forgery detection using undecimated dyadic wavelet transform. Digital Investig. 9, 49-57 (2012)
40. Martin, D.; Fowlkes, C.; Malik, J.: Learning to detect natural image boundaries using local brightness, color and texture cues. IEEE Trans. Pattern Anal. Mach. Intell. 26(5), 530-549 (2004)