COVERAGE — A novel database for copy-move forgery detection
Abstract
We present COVERAGE - a novel database containing copy-move forged images and their originals with similar but genuine objects. COVERAGE is designed to highlight and address tamper detection ambiguity of popular methods, caused by self-similarity within natural images. In COVERAGE, forged-original pairs are annotated with (i) the duplicated and forged region masks, and (ii) the tampering factor/similarity metric. For benchmarking, forgery quality is evaluated using (i) computer vision-based methods, and (ii) human detection performance. We also propose a novel sparsity-based metric for efficiently estimating forgery quality. Experimental results show that (a) popular forgery detection methods perform poorly over COVERAGE, and (b) the proposed sparsity based metric best correlates with human detection performance. We release the COVERAGE database to the research community.
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BioFors has real-world suspicious images where the forgeries are diverse and the image creators do not share the origin of images or manipulation.
“Unlike natural-image forensic datasets [33, 50, 1, 16] that include synthetic manipulations, BioFors has realworld suspicious images where the forgeries are diverse and the image creators do not share the origin of images or manipulation.”
From BioFors: A Large Biomedical Image Forensics Dataset (2021) · cites this paper as [50]
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Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892 · see citing works
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Media Forensics and DeepFakes: An Overview
Verdoliva, L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.3002101 · Cited by 979 · see citing works
A Serial Image Copy-Move Forgery Localization Scheme With Source/Target Distinguishment
Chen, B., Tan, W., Coatrieux, G., Zheng, Y., & Shi, Y.-Q. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3026868 · Cited by 159 · see citing works
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 · see citing works
A Self-Supervised Descriptor for Image Copy Detection
Pizzi, E., Roy, S. D., Ravindra, S. N., Goyal, P., & Douze, M. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01413 · Cited by 101 · see citing works
Kadam, K. D., Ahirrao, S., & Kotecha, K. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/6845326 · Cited by 59 · see citing works
RetractedToward real text manipulation detection: New dataset and new solution
Luo, D., Liu, Y., Yang, R., Liu, X., Zeng, J., Zhou, Y., & Bai, X. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2024.110828 · Cited by 25 · see citing works
BioFors: A Large Biomedical Image Forensics Dataset
Sabir, E., Nandi, S., AbdAlmageed, W., & Natarajan, P. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01078 · Cited by 12 · see citing works
“Similarly, CASIA [16], NIST16 [1], COLUMBIA [33] and COVERAGE [50] helped advance detection methods for a combination of forgeries such as copy-move, splicing and removal.”
BackgroundMethod
- Authors
- Wen, B., Zhu, Y., Subramanian, R., Ng, T.-T., Shen, X., & Winkler, S.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Institute for Infocomm Research (SG)
- International Institute of Information Technology, Hyderabad (IN)
- Jilin University (CN)
- Venue
- 2016 IEEE International Conference on Image Processing (ICIP)
- Publisher
- IEEE
- Published
- 2016-09
- Pages
- 161-165
- ISSN
- 1522-4880 (ISSN-L)
- OpenAlex
- W2518397542
- Cited by
- 440
- References
- 1
- Citations by year
- 2026: 53 · 2025: 88 · 2024: 98 · 2023: 62 · 2022: 47 · 2021: 35 · 2020: 23 · 2019: 23 · 2018: 4 · 2017: 5 · 2016: 2
- FWCI
- 3.93
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings - International Conference on Image Processing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Benford’s Law and Fraud Detection
- Keywords
- copy-move forgery detection, image tamper detection, coverage database
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