Abstract
Due to the availability of media editing software, the authenticity and reliability of digital images are important. Region manipulation is a simple and effective method for digital image forgeries. Hence, the potential to identify the image manipulation is current research issue these days and copy–move forgery detection (CMFD) is a main domain in image authentication. In copy–move forgery, one region is simply copied and pasted over other region in the same image for manipulating the image. In this paper, we have proposed a method based on Harris corner and adaptive non-maximal Suppression (ANMS). Initially, the input image is taken, and then Harris corner detection algorithm is used to detect the interest points, and ANMS is adopted to control the number of Harris points in an image. This gives an appropriate number of interest points for different size of images and gives the assurance for finding the manipulated region in manageable time. For each extracted interest point, SIFT is used for calculating the descriptors. Now obtained descriptors are matched using the outlier rejection with nearest neighbour. Here RANSAC is used to find the best set of matches to identify the manipulated regions. Experimental results show the robustness against different transformation and post-processing operations.
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References
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 (2011)
Bo, X., Junwen, W., Guangjie, L., Yuewei, D.: Image copy-move forgery detection based on surf. In: 2010 international conference on Multimedia information networking and security (MINES), pp. 889–892. IEEE (2010)
Brown, M., Lowe, D.G.: Invariant features from interest point groups. In: BMVC, vol. 4 (2002)
Brown, M., Lowe, D.G.: Automatic panoramic image stitching using invariant features. Int. J. Comput. Vis. 74(1), 59–73 (2007)
Chen, L., Lu, W., Ni, J., Sun, W., Huang, J.: Region duplication detection based on harris corner points and step sector statistics. J. Vis. Commun. Image Represent. 24(3), 244–254 (2013)
Christlein, V., Riess, C., Jordan, J., Riess, C., Angelopoulou, E.: An evaluation of popular copy-move forgery detection approaches. IEEE Trans. Inf. Forensics Secur. 7(6), 1841–1854 (2012)
Fridrich, A.J., Soukal, B.D., Lukáš, A.J.: Detection of copy-move forgery in digital images. In: Proceedings of Digital Forensic Research Workshop. Citeseer (2003)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Alvey Vision Conference. vol. 15, pp. 10–5244. Citeseer (1988)
Huang, H., Guo, W., Zhang, Y.: Detection of copy-move forgery in digital images using sift algorithm. In: Computational Intelligence and Industrial Application, 2008. PACIIA’08. Pacific-Asia Workshop on. vol. 2, pp. 272–276. IEEE (2008)
Kang, X., Wei, S.: Identifying tampered regions using singular value decomposition in digital image forensics. In: 2008 International Conference on Computer Science and Software Engineering, vol. 3, pp. 926–930. IEEE (2008)
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: 2007 IEEE International Conference on Multimedia and Expo, pp. 1750–1753. IEEE (2007)
Luo, W., Huang, J., Qiu, G.: Robust detection of region-duplication forgery in digital image. In: 18th International Conference on Pattern Recognition, 2006. ICPR 2006. vol. 4, pp. 746–749. IEEE (2006)
Mahdian, B., Saic, S.: Detection of copy-move forgery using a method based on blur moment invariants. Forensic Sci. Int. 171(2), 180–189 (2007)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
Moravec, H.P.: Obstacle avoidance and navigation in the real world by a seeing robot rover. Technical report, DTIC Document (1980)
Pan, X., Lyu, S.: Detecting image region duplication using sift features. In: 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 1706–1709. IEEE (2010)
Pan, X., Lyu, S.: Region duplication detection using image feature matching. IEEE Trans. Inf. Forensics Secur. 5(4), 857–867 (2010)
Popescu, A., Farid, H.: Exposing digital forgeries by detecting duplicated image region [technical report]. 2004–515. Hanover, Department of Computer Science, Dartmouth College. USA p. 32 (2004)
Shivakumar, B., Baboo, L.D.S.S.: Detection of region duplication forgery in digital images using surf. IJCSI Int. J. Comput. Sci. Issues 8(4) (2011)
Silva, E., Carvalho, T., Ferreira, A., Rocha, A.: Going deeper into copy-move forgery detection: exploring image telltales via multi-scale analysis and voting processes. J. Vis. Commun. Image Represent. 29, 16–32 (2015)
Tralic, D., Zupancic, I., Grgic, S., Grgic, M.: CoMoFod new database for copy-move forgery detection. In: ELMAR, 2013 55th International Symposium, pp. 49–54. IEEE (2013)
Zhang, J., Feng, Z., Su, Y.: A new approach for detecting copy-move forgery in digital images. In: 11th IEEE Singapore International Conference on Communication Systems, 2008. ICCS 2008, pp. 362–366. IEEE (2008)
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Shyam Prakash, C., Maheshkar, S., Maheshkar, V. (2018). Image Manipulation Detection Using Harris Corner and ANMS. In: Reddy Edla, D., Lingras, P., Venkatanareshbabu K. (eds) Advances in Machine Learning and Data Science. Advances in Intelligent Systems and Computing, vol 705. Springer, Singapore. https://doi.org/10.1007/978-981-10-8569-7_9
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DOI: https://doi.org/10.1007/978-981-10-8569-7_9
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