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CASIA Image Tampering Detection Evaluation Database

Dong, Jing, Wang, Wei, Tan, Tieniu·2013·2013 IEEE China Summit and International Conference on Signal and Information Processing

Abstract

Image forensics has now raised the anxiety of justice as increasing cases of abusing tampered images in newspapers and court for evidence are reported recently. With the goal of verifying image content authenticity, passive-blind image tampering detection is called for. More realistic open benchmark databases are also needed to assist the techniques. Recently, we collect a natural color image database with realistic tampering operations. The database is made publicly available for researchers to compare and evaluate their proposed tampering detection techniques. We call this database CASI-A Image Tampering Detection Evaluation Database. We describe the purpose, the design criterion, the organization and self-evaluation of this database in this paper.

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Research works printed but not linked: 14

  1. 10.1109/ICIP.2009.5414611 · DOI · Paper page
  2. ng, 2004, A Data Set of Au-thentic and Spliced Image Blocks
  3. 10.1109/TIFS.2007.916285 · DOI · Paper page
  4. sencar, 0, Discrimination of computer synthesized or recaptured images from real images, IEEE International Con-ference on Acoustics Speech and Signal Processing Taipei Taiwan, 1053
  5. 10.1109/MSP.2008.931079 · DOI · Paper page
  6. wang, 2009, A survey of passive image tampering detection, 8th Internation-al Workshop on Digital Watermarking, 308, 10.1007/978-3-642-03688-0_27 · DOI
  7. farid, 0, Examples of Photo Tampering Throughout History
  8. 10.1109/CISS.2006.286646 · DOI
  9. qu, 2009, Detec-t digital image splicing with visual cues, 11th In-ternational Workshop on Information Hiding, 247, 10.1007/978-3-642-04431-1_18 · DOI
  10. 10.1109/ICASSP.2009.4959768 · DOI · Paper page
  11. 10.1117/12.838888 · doi:10.1117/12.838888
  12. farid, 0, Digital Forensic Database
  13. cao, 0, Edge-based blur metric for tamper detection, Journal of Infor-mation Hiding and Multimedia Signal Processing, 11, 20
  14. 10.1109/ICIP.2009.5413549 · DOI

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Metadata

Authors
Dong, J., Wang, W., & Tan, T.
Venue
2013 IEEE China Summit and International Conference on Signal and Information Processing
Publisher
IEEE
Published
2013-07
Pages
422-426
OpenAlex
W2169439181
Cited by
813
References
0
FWCI
2.35
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: CASIA Image Tampering Detection Evaluation Database. https://app.cochat.ai/papers/10.1109/chinasip.2013.6625374
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Dong, J., Wang, W., & Tan, T. (2013). CASIA Image Tampering Detection Evaluation Database. 2013 IEEE China Summit and International Conference on Signal and Information Processing. https://doi.org/10.1109/chinasip.2013.6625374

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