The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The 'Dresden Image Database' for benchmarking digital image forensics
Abstract
This paper introduces and documents a novel image database specifically built for the purpose of development and bench-marking of camera-based digital forensic techniques. More than 14,000 images of various indoor and outdoor scenes have been acquired under controlled and thus widely comparable conditions from altogether 73 digital cameras. The cameras were drawn from only 25 different models to ensure that device-specific and model-specific characteristics can be disentangled and studied separately, as validated with results in this paper. In addition, auxiliary images for the estimation of device-specific sensor noise pattern were collected for each camera. Another subset of images to study model-specific JPEG compression algorithms has been compiled for each model. The 'Dresden Image Database' will be made freely available for scientific purposes when this accompanying paper is presented. The database is intended to become a useful resource for researchers and forensic investigators. Using a standard database as a benchmark not only makes results more comparable and reproducible, but it is also more economical and avoids potential copyright and privacy issues that go along with self-sampled benchmark sets from public photo communities on the Internet.
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Cites
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
Cited by
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
An Evaluation of Popular Copy-Move Forgery Detection Approaches
Christlein, V., Riess, C., Jordan, J., Riess, C., & Angelopoulou, E. (2012) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2012.2218597 · Cited by 802
RAISE: a raw images dataset for digital image forensics
Dang-Nguyen, D.-T., Pasquini, C., Conotter, V., & Boato, G. (2015) · Proceedings of the 6th ACM Multimedia Systems Conference · doi:10.1145/2713168.2713194 · Cited by 508
Noiseprint: A CNN-Based Camera Model Fingerprint
Cozzolino, D., & Verdoliva, L. (2020) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2916364 · Cited by 499
MFC Datasets: Large-Scale Benchmark Datasets for Media Forensic Challenge Evaluation
Guan, H., Kozak, M., Robertson, E., Lee, Y., Yates, A. N., Delgado, A., Zhou, D., Kheyrkhah, T., Smith, J., & Fiscus, J. (2019) · 2019 IEEE Winter Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw.2019.00018 · Cited by 329
Metadata
- Authors
- Gloe, T., & Böhme, R.
- Venue
- Proceedings of the 2010 ACM Symposium on Applied Computing
- Publisher
- ACM
- Published
- 2010-03-22
- Pages
- 1584-1590
- OpenAlex
- W2049771774
- Cited by
- 388
- References
- 1
- FWCI
- 8.25
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Gloe, T., & Böhme, R. (2010). The 'Dresden Image Database' for benchmarking digital image forensics. Proceedings of the 2010 ACM Symposium on Applied Computing. https://doi.org/10.1145/1774088.1774427
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