Abstract
The issue of verifying the authenticity and integrity of digital images is becoming increasingly important. Copy-move forgery is one type of image tempering that is commonly used for manipulating digital content; in this case, some part of an image is copied and pasted on another region of the image. Using a non-intrusive approach to solve this problem is becoming attractive because it does not need any embedded information, but it is still far from being satisfactory. In this paper, an efficient non-intrusive method for copy-move forgery detection is presented. The method is based on image segmentation and a new denoising algorithm. First, the image is segmented using a multi-scale segmentation algorithm. Then, using the noise pattern of each segment, a separate noise image is created. The noise images are used to estimate the overall noise of the image which is further used to re-estimate the noise pattern of different segments. The image segments with similar noise histograms are detected as tampered. A comparison with a state-of-the art non-intrusive algorithm shows that the proposed method performs better.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bayram, S., Sencar, H.T., Memon, N.: An Efficient and Robust Method for Detecting Copy-Move Forgery. In: Proc. IEEE ICASSP, pp. 1053–1056 (2009)
Chen, M., et al.: Determining Image Origin and Integrity Using Sensor Noise. IEEE Transactions on Information Forensics and Security, 74–90 (2008)
Fridrich, J., Soukal, D., Lukas, J.: Detection of Copy Move Forgery in Digital Images. In: Digital Forensic Research Workshop, Cleveland, OH (2003)
Huang, H., et al.: Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm. In: Pacific-Asia Workshop on Computational Intell. Industrial App., pp. 272–276 (2008)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 2nd edn., Section 8.2: Counting sort, pp. 168–170. MIT Press and McGraw-Hill (2001)
Kang, X., Wei, S.: Identifying Tampered regions using singular value decomposition in Digital image forensics, pp. 926–930. IEEE Computer Society, USA (2008)
Li, Y., Li, C.-T.: Decomposed Photo Response Non-Uniformity for Digital Forensic Analysis. In: Sorell, M. (ed.) e-Forensics 2009. LNICST, vol. 8, pp. 166–172. Springer, Heidelberg (2009)
Lin, H.-J., Wang, C.-W., Kao, Y.-T.: Fast Copy-Move Forgery Detection. WSEAS Trans. Signal Process, 188–197 (2009)
Lin, H.J., Wang, C.W.,, Y.: Fast Copy-Move Forgery Detection. In: World Scientific and Engineering Academy and Society (WSEAS), pp. 188–197 (2009)
Lukáš, J., et al.: Detecting Digital Image Forgeries Using Sensor Pattern Noise. In: Proc. of SPIE (2006)
Mahdian, B., Saic, S.: Detection of Copy Move Forgery Using a Method Based on Blur Moment Invariants. Forensic Science International 171, 180–189 (2007)
Mahdian, B., Saic, S.: Using Noise Inconsistencies for Blind Image Forensics. Image and Vision Computing, 1497–1503 (2009)
Popescu, A.C., Farid, H.: Exposing Digital Forgeries by Detecting Duplicated Image Regions. Dept. Comput. Sci., Dartmouth College,Tech.Rep. TR2004-515 (2004)
Sutcu, Y., et al.: Tamper Detection Based on Regularity of Wavelet Transform Coefficients. In: Proc. IEEE ICIP, pp. 397–400 (2007)
Wang, J., et al.: Detection of Image Region Duplication Forgery Using Model with Circle Block. In: International Conf. Multimedia Inform. Network. and Security, pp. 25–29 (2009)
Zhang, J., Feng, Z., Su, Y.: A New Approach for Detecting Copy-Move Forgery in Digital Images. In: IEEE Singapore Int. Conf. Comm. Sys., China, pp. 362–366 (2008)
Zhang, P., Kong, X.: Detecting Image Tampering Using Feature Fusion. In: International Conference on Availability, Reliability and Security, pp. 335–340 (2009)
Cour, T., et al.: Spectral Segmentation with Multiscale Graph Decomposition. In: IEEE International Conference on Computer Vision and Pattern Recognition, CVPR (2005)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Muhammad, N., Hussain, M., Muhamad, G., Bebis, G. (2011). A Non-intrusive Method for Copy-Move Forgery Detection. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6939. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24031-7_52
Download citation
DOI: https://doi.org/10.1007/978-3-642-24031-7_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24030-0
Online ISBN: 978-3-642-24031-7
eBook Packages: Computer ScienceComputer Science (R0)