SCCRNet: a framework for source camera identification on digital images
Author:
Funder
Centre for Engineering Research and Development
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09088-6.pdf
Reference44 articles.
1. Lyu S (2006) Digital image forensics: there is more to a picture than meets the eye
2. San CK, Lam EY, Wong KK (2006) Source camera identification using footprints from lens aberration. In: SPIE, 6069:60690 . https://doi.org/10.1117/12.649775
3. Çeliktutan O, Sankur B, Avcibas I (2008) Blind identification of source cell-phone model. IEEE Trans Inf For Secur 3(3):553–566. https://doi.org/10.1109/TIFS.2008.926993
4. Korus P (2017) Digital image integrity-a survey of protection and verification techniques. Digital Signal Process 71:1–26. https://doi.org/10.1016/j.dsp.2017.08.009
5. Bernacki J (2020) A survey on digital camera identification methods. For Sci Int Digit Investig 34:300983. https://doi.org/10.1016/j.fsidi.2020.300983
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