Abstract
With the advancements in computer technology digital image tampering like copy-move forgery has become frequent. In this paper, we present a novel DCT-based technique for detecting copy-move forgery. DCT is applied to each fixed-size overlapping block of image to represent its features. The dimension of the features is reduced using truncation. Then the feature vectors are lexicographically sorted and, duplicated image blocks will be neighboring in the sorted list. Thus duplicated image blocks will be compared in the matching step. To make the method more robust, a scheme to judge whether two feature vectors are similar is imported. Simulation results show that the proposed technique is capable of detecting the duplicated regions even when an image was distorted by JPEG compression, blurring or additive white Gaussian noise.
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References
Bayram, S., Sencar, H.T., Memon, N.: An efficient and robust method for detecting copy-move forgery. In: ICASSP 2009. IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, pp. 1053–1056. IEEE (2009)
Farid, A., Popescu, A.: Exposing digital forgeries by detecting duplicated image regions. Technical Report, TR2004-515, Department of Computer Science, Dartmouth College, Hanover, New Hampshire (2004)
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)
Gonzalez, R.: Re Woods, Digital Image Processing. Addison (1992)
Huang, Y., Lu, W., Sun, W., Long, D.: Improved DCT-based detection of copy-move forgery in images. Forensic Sci. Int. 206(1), 178–184 (2011)
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)
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)
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© 2017 Springer Science+Business Media Singapore
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Prakash, C.S., Anand, K.V., Maheshkar, S. (2017). Detection of Copy-Move Image Forgery Using DCT. In: Sahana, S.K., Saha, S.K. (eds) Advances in Computational Intelligence. ICCI 2015. Advances in Intelligent Systems and Computing, vol 509. Springer, Singapore. https://doi.org/10.1007/978-981-10-2525-9_25
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DOI: https://doi.org/10.1007/978-981-10-2525-9_25
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-10-2525-9
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