The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Copy-move forgery detection and localization by means of robust clustering with J-Linkage
Open accessAbstract
Understanding if a digital image is authentic or not, is a key purpose of image forensics. There are several different tampering attacks but, surely, one of the most common and immediate one is copy-move. A recent and effective approach for detecting copy-move forgeries is to use local visual features such as SIFT. In this kind of methods, SIFT matching is often followed by a clustering procedure to group keypoints that are spatially close. Often, this procedure could be unsatisfactory, in particular in those cases in which the copied patch contains pixels that are spatially very distant among them, and when the pasted area is near to the original source. In such cases, a better estimation of the cloned area is necessary in order to obtain an accurate forgery localization. In this paper a novel approach is presented for copy-move forgery detection and localization based on the JLinkage algorithm, which performs a robust clustering in the space of the geometric transformation. Experimental results, carried out on different datasets, show that the proposed method outperforms other similar state-of-the-art techniques both in terms of copy-move forgery detection reliability and of precision in the manipulated patch localization.
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Citations
Cites
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Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
A SIFT-Based Forensic Method for Copy–Move Attack Detection and Transformation Recovery
Amerini, I., Ballan, L., Caldelli, R., Del Bimbo, A., & Serra, G. (2011) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2011.2129512 · Cited by 1,044
Self-citationDetection of Copy-Move Forgery in Digital Images
Fridrich, J. (2004) · Cited by 1,040
Farid, H. (2009) · IEEE Signal Processing Magazine · doi:10.1109/msp.2008.931079 · Cited by 925
Exposing Digital Forgeries by Detecting Duplicated Image Regions
Popescu, A., & Farid, H. (2004) · Cited by 641
An efficient and robust method for detecting copy-move forgery
Bayram, S., Taha Sencar, H., & Memon, N. (2009) · 2009 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2009.4959768 · Cited by 491
Region Duplication Detection Using Image Feature Matching
Pan, X., & Lyu, S. (2010) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2010.2078506 · Cited by 421
Detection of copy–move forgery using a method based on blur moment invariants
Mahdian, B., & Saic, S. (2007) · Forensic Science International · doi:10.1016/j.forsciint.2006.11.002 · Cited by 414
Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis
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Cited by
Efficient Dense-Field Copy–Move Forgery Detection
Cozzolino, D., Poggi, G., & Verdoliva, L. (2015) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2455334 · Cited by 451
Copy–Move Forgery Detection by Matching Triangles of Keypoints
Ardizzone, E., Bruno, A., & Mazzola, G. (2015) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2445742 · Cited by 266
A detailed analysis of image and video forgery detection techniques
Tyagi, S., & Yadav, D. (2023) · The Visual Computer · doi:10.1007/s00371-021-02347-4 · Cited by 109
Security in smart cities: A brief review of digital forensic schemes for biometric data
Ross, A., Banerjee, S., & Chowdhury, A. (2020) · Pattern Recognition Letters · doi:10.1016/j.patrec.2020.07.009 · Cited by 85
Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers
Diel, A., Lalgi, T., Schröter, I. C., MacDorman, K. F., Teufel, M., & Bäuerle, A. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100538 · Cited by 64
Metadata
- Authors
- Amerini, I., Ballan, L., Caldelli, R., Del Bimbo, A., Del Tongo, L., & Serra, G.
- Venue
- Signal Processing: Image Communication
- Publisher
- Elsevier BV
- Published
- 2013-07
- Volume
- 28
- Issue
- 6
- Pages
- 659-669
- ISSN
- 0923-5965 (ISSN-L)
- OpenAlex
- W1987535593
- Cited by
- 302
- References
- 29
- FWCI
- 22.30
- Type
- journal article
- Language
- en
- Open access
- green
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- Amerini, I., Ballan, L., Caldelli, R., Del Bimbo, A., Del Tongo, L., & Serra, G. (2013). Copy-move forgery detection and localization by means of robust clustering with J-Linkage. Signal Processing: Image Communication. https://doi.org/10.1016/j.image.2013.03.006
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