Abstract
Digital images are easy to be tempered and edited due to availability of image editing software. The most common ways to temper a digital image is copy-paste forgery which is used to conceal objects or produce a non-existing scene. To detect the copy-paste forgery, we divide the image into blocks as the basic feature for detection, and transfer every block to a feature vector with lower dimension for comparison. The number of blocks and dimension of characteristics are the major factor affecting the computation complexity. In this paper, we modify the previous methods by using less cumulative offsets for block matching. The experimental results show that our method can successfully detect the forgery part even when the forged image is saved in a lossy format such as JPEG. The performance of the proposed method is demonstrated on several forged images.
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
Zhu, B.B., Swanson, M.D., Tewfik, A.H.: When Seeing isn’t Believing. IEEE Signal Processing (March 2004)
Ng, T.-T., Chang, S.-F., Sun, Q.: Blind Detection of Photomontage Using Higher Order Statistics. In: IEEE International Symposium on Circuits and Systems, Vancouver, Canada (May 2004)
Fridrich, J., Soukal, D., Lukas, J.: Detection of copy-move forgery in digital images. In: Proceedings of Digital Forensic Research Workshop (August 2003)
Popescu, A., Farid, H.: Exposing Digital Forgeries by Detecting Duplicated Image Regions, Computer Science, Dartmouth College, Tech. Rep. TR2004-515,2004
Li, G.H., Wu, Q., Tu, D., Sun, S.J.: A sorted neighborhood approach for detecting duplicated regions in image forgeries based on DWT and SVD. In: Proceedings of 2007 IEEE ICME, pp. 1750–1753. IEEE, Beijing (2007)
Graps, A.: An Introduction to Wavelets. IEEE Computational Science and Engineering 2(2), 50–61 (1992)
Ientilucci, E.J.: Using the Singular Value Decompostion., Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, May 29 (2003)
Elmagarmid, A.K., Ipeirotis, P.G.: Duplicate Record Detection: A Survey. IEEE Transactions on Knowledge and Data Engineering 19(1) (January 2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, QC., Huang, CL. (2009). Copy-Move Forgery Detection in Digital Image. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_72
Download citation
DOI: https://doi.org/10.1007/978-3-642-10467-1_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10466-4
Online ISBN: 978-3-642-10467-1
eBook Packages: Computer ScienceComputer Science (R0)