{"title":"DWT-SATS Based Detection of Image Region Cloning ","authors":"Michael Zimba ","volume":86,"journal":"International Journal of Computer and Information Engineering","pagesStart":271,"pagesEnd":277,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/9997360","abstract":"
A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency subband of the DWT of the suspicious image thereby leaving valuable information in the other three subbands, the proposed algorithm simultaneously extracts features from all the four subbands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates. <\/p>\r\n","references":"[1]\tH. Farid, \"A Survey of Image Forgery Detection,\u201d in Signal Proc. Magazine, vol. 26, no. 2, 2009, pp.16-25.\r\n[2]\tA.C. Popescu and H. Farid, \"Exposing Digital Forgeries by Detecting Traces of Resampling\u201d, IEEE Trans. Signal Processing, vol. 53, pp. 758-767, 2005.\r\n[3]\tH. Sencar and N. Memon, \"Overview of State- of- the- art in Digital Image Forensics,\u201d Algorithms, Architectures and Information Systems Security, pp. 325-344, 2008. \r\n[4]\tT. Ng, S. Chang, C. Lin, and Q. Sun, \"Passive-Blind Image Forensics,\u201d Multimedia Security Technologies for Digital Rights Management, Academic Press, pp. 383-412, 2006\r\n[5]\tM. Zimba and S. Xingming, \"DWT-PCA (EVD) Based Copy-move Image Forgery,\u201d JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 1, 2011, pp.251-258.\r\n[6]\tN. Wandjie, S. Xingming and M. Kue, \"Detection of Copy-move Forgery in Digital Images based on DCT,\u201dIJCSI, Vol. 10, No 1, 2013, pp. 295-302.\r\n[7]\tW. Luo, J. Huang, and G. Qui, \"Robust Detection of Region Duplication Forgery in Digital Image,\u201d Proceedings of the 18th International Conference on Pattern Recognition, Vol. 4, 2006, pp. 746-749.\r\n[8]\tH.J. Lin, C.W. Wang, and Y.T. Kao, \"Fast Copy-Move Forgery Detection,\u201d WSEAS Transactions on Signal Processing, Vol. 5, No. 5, 2009, pp.188-197\r\n[9]\tI.T. Joliffe Principal Component Analysis, Springer-Verlag New Yolk, 2nd edition, 2002, ch.1-4.\r\n[10]\tI. Amerini, L. Ballan, R. Caldelli, A.D. Bimbo and G. Serra, \"Geometric Tampering Estimation by Means of a Sift-Based Forensic Analysis,\u201d International Conf. Acoustic Speech and Signal Processing, Dallas TX, USA, March 14-19, 2010.\r\n[11]\tR.I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2nd edition, 2004\r\n[12]\tA.V. Christlein, C. Riess and E. Angelopoulou, \"On Rotation Invariance in Copy-Move Forgery Detection,\u201d in Proc. IEEE Workshop, Information Forensics and Security, Seattle USA, 2010\r\n[13]\tM. Zimba and D. Nyirenda, \"Copy-Move Image Forgery Detection in Virtual Electrostatic Field\u201d ICECSP 2013: International Conference on Electronics, Control and Signal Processing, Cape Town, South Africa, November (20-21), 2013, pp. 925-932.\r\n[14]\tM. Zimba and S. Xingming, \"Fast and Robust Image Cloning Detection Using Block Characteristics of DWT Coefficients,\u201d JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 7, 2011, pp.359-367\r\n[15]\tC. Riess and E. Angelopoulou, \"Scene Illumination as an Indicator of Image Manipulation,\u201d 12th International Workshop on Information Hiding, Springer, Vol. 6387, 2010, pp. 66-80\r\n[16]\tG. Li, Q. Wu, D. Tu, and S. Sun, \"A Sorted Neighborhood Approach for Detecting Duplicated Regions in Image Forgeries based on DWT and SVD,\u201d in Proc. IEEE International Conf. Multimedia and Expo, Beijing China, 2007, pp. 1750-1753.\r\n","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 86, 2014"}