An improved surveillance video forgery detection technique using sensor pattern noise and correlation of noise residues
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
http://link.springer.com/content/pdf/10.1007/s11042-019-08236-2.pdf
Reference38 articles.
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2. Ba Z, Qin Z, Fu X, Ren K (2019) CIM: camera in motion for smartphone authentication. IEEE Trans Inf Forensics Secur 14(11):2987–3002
3. Bestagini P, Milani S, Tagliasacchi M, Tubaro S (2013) Local tampering detection invideo sequences. In: 2013 IEEE 15th international workshop on multimedia signal processing (MMSP), pp 488–493
4. Cooper AJ (2013) Improved photo response non-uniformity (PRNU) based source camera identification. Forensic Sci Int 226(1–3), 132–141.
5. Fadl SM, Han Q, Li Q (2018) Authentication of surveillance videos: detecting frame duplication based on residual frame. J Forensic Sci 63(4):1099–1109
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