Non-overlapping block-level difference-based image forgery detection and localization (NB-localization)
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-022-02710-z.pdf
Reference61 articles.
1. Jain, I., Goel, N.: Advancements in image splicing and copy-move forgery detection techniques: a survey (2021). https://doi.org/10.1109/Confluence51648.2021.9377104
2. Tyagi, S., Yadav, D.: A detailed analysis of image and video forgery detection techniques. Vis. Comput. (2022). https://doi.org/10.1007/s00371-021-02347-4
3. Santhosh Kumar, B., Karthi, S., Karthika, K., Cristin, R.: A systematic study of image forgery detection. J. Comput. Theor. Nanosci. (2018). https://doi.org/10.1166/jctn.2018.7498
4. Swain, M., Swain, D.: An effective watermarking technique using BTC and SVD for image authentication and quality recovery. Integration (2022). https://doi.org/10.1016/j.vlsi.2021.11.004
5. Manjunatha, S., Patil, M.M.: A study on image forgery detection techniques. CiiT Int. J. Digit. Image Process. 9(5) 2017
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1. Image Manipulation Detection and Classification Using SIFT and SURF with Support Vector Machine Classifier;2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC);2023-12-04
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