Abstract
Copy-Move in an image might be done to duplicate something or to hide an undesirable region. So in this paper we propose a novel method to detect copy-move forgery detection (CMFD) using Speed-Up Robust Features (SURF), Histogram Oriented Gradient (HOG) and Scale Invariant Features Transform (SIFT), image features. SIFT and SURF image features are immune to various transformations like rotation, scaling, translation etc., so SIFT and SURF image features help in detecting Copy-Move regions more accurately in compared to other image features. We have compared our method for different features and SIFT features show better results among them. For enhancement of performance and complete localization to Copy Move region, a hybrid SURF-HOG and SIFT-HOG features are considered for CMFD. We are getting commendable results for CMFD using hybrid features.
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References
Lyu, S., Farid, H.: How realistic is photorealistic? IEEE Transactions on Signal Processing 53(2), 845–850 (2005)
Farid, H.: Photo fakery and forensics. Advances in Computers 77, 1–55 (2009)
Redi, J.A., Taktak, W., Dugelay, J.L.: Digital image forensics, a booklet for beginners. Multimedia Tools and Applications 51(1), 133–162 (2011)
Cox, I.J., Miller, M.L., Bloom, J.A.: Digital watermarking. Morgan Kaufmann, San Francisco (2002)
Barni, M., Bartolini, F.: Watermarking Systems Engineering: Enabling Digital Assets Security and Other Applications. Marcel Dekker (2004)
Farid, H.: A survey of image forgery detection. IEEE Signal Processing Magazine 2(26), 16–25 (2009)
Popescu, A., Farid, H.: Statistical tools for digital forensics. In: Proc. of Int.’l Workshop on Information Hiding, Toronto, Canada (2005)
Swaminathan, A., Wu, M., Liu, K.: Digital image forensics via intrinsic fingerprints. IEEE Transactions on Information Forensics and Security 3(1), 101–117 (2008)
Chen, M., Fridrich, J., Goljan, M., Lukas, J.: Determining image origin and integrity using sensor noise. IEEE Transactions on Information Forensics and Security 3(1), 74–90 (2008)
Khanna, N., Chiu, G.T.C., Allebach, J.P., Delp, E.J.: Forensic techniques for classifying scanner, computer generated and digital camera images. In: Proc. of IEEE ICASSP, Las Vegas, USA (2008)
Caldelli, R., Amerini, I., Picchioni, F.: A DFT-based analysis to discern between camera and scanned images. International Journal of Digital Crime and Forensics 2(1), 21–29 (2010)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int.’l Journal of Computer Vision 60(2), 91–110 (2004)
Popescu, A., Farid, H.: Exposing digital forgeries by detecting duplicated image regions, Dartmouth College, Computer Science, Tech. Rep. TR2004-515 (2004)
Bayram, S., Sencar, H.T., Memon, N.: An efficient and robust method for detecting copy-move forgery. In: Proc. of IEEE ICASSP, Washington, DC, USA (2009)
Bayram, S., Sencar, H.T., Memon, N.: A survey of copy-move forgery detection techniques. In: Proc. of IEEE Western New York Image Processing Workshop, Rochester, NY (2008)
Bay, H., Tuytelaars, T., Gool, L.-V.: SURF: Speeded Up Robust Features. In: Proc. of ETH Zurich (2006)
Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. In: Proc. of INRIA Rhone-Alps, 655 avenue de l’Europe, Montbonnot 38334, France (2005)
Amerini, I., Ballan, L., Caldelli, R., Bimbo, A.D.: A SIFT-based forensic method for copy-move attack detection and transformation recovery. In: Proc. of IEEE Transactions on Information Forensics and Security (2011)
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Pandey, R.C., Agrawal, R., Singh, S.K., Shukla, K.K. (2015). Passive Copy Move Forgery Detection Using SURF, HOG and SIFT Features. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_74
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DOI: https://doi.org/10.1007/978-3-319-11933-5_74
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11932-8
Online ISBN: 978-3-319-11933-5
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