Splicing image forgery detection using textural features based on the grey level co‐occurrence matrices
Author:
Affiliation:
1. College of Computer Science and Technology, Jilin UniversityChangchunPeople's Republic of China
2. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchunPeople's Republic of China
Funder
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2016.0238
Reference31 articles.
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4. Combining spatial and DCT based Markov features for enhanced blind detection of image splicing;El‐Alfy E.S.M.;Formal Pattern Anal. Applications,2014
5. Digital image splicing detection based on approximate run length;He Z.;Pattern Recognit. Lett.,2011
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