Binary multi-view perceptual hashing for image authentication
Author:
Funder
Young Scientists Fund
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-020-08736-6.pdf
Reference81 articles.
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2. Anitha K and Leveenbose P (2015) “Edge detection based salient region detection for accurate image forgery detection,” in IEEE International Conference on Computational Intelligence and Computing Research, pp. 1–4
3. Bondi L, Lameri S, Guera D, Bestagini P, Delp EJ, and Tubaro S (2017) “Tampering detection and localization through clustering of camera-based cnn features,” 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1855–1864
4. Brbi M, Kopriva I (2018) Multi-view low-rank sparse subspace clustering. Pattern Recogn 73(2):247–258
5. Chen Y, Yu W, Feng J (2014) Robust image hashing using invariants of tchebichef moments. Optik - International Journal for Light and Electron Optics 125(19):5582–5587
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