Exposing digital image forgeries from statistical footprints-Reference-Cited by-同舟云学术

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Exposing digital image forgeries from statistical footprints

Published:2022-09 Issue: Volume:69 Page:103273
ISSN:2214-2126
Container-title:Journal of Information Security and Applications
language:en
Short-container-title:Journal of Information Security and Applications

Author:

Bharathiraja S.,Kanna B. Rajesh^ORCID,Geetha S.,Hariharan M.

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality,Software

Reference21 articles.

1. An efficient and robust method for detecting copy-move forgery;Bayram,2009

2. Can we trust digital image forensics?;Gloe,2007

3. Anti-forensics of digital image compression;Stamm,2011

4. Forensic detection of image manipulation using statistical intrinsic fingerprints;Stamm,2010

5. Anti-forensics of median filtering and contrast enhancement;Sharma,2020

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning-based efficient and robust image forgery detection;Multimedia Tools and Applications;2024-01-02

2. Unmasking the digital deception - a comprehensive survey on image forgery and detection techniques;Australian Journal of Forensic Sciences;2023-11-15

3. MCDC‐Net: Multi‐scale forgery image detection network based on central difference convolution;IET Image Processing;2023-09-17

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