Open AccessCMFD: a detailed review of block based and key feature based techniques in image copy‐move forgery detection
Author(s) -
Soni Badal,
Das Pradip K.,
Thounaojam Dalton Meitei
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0441
Subject(s) - computer science , block (permutation group theory) , image (mathematics) , key (lock) , feature (linguistics) , artificial intelligence , computer vision , domain (mathematical analysis) , image manipulation , computer security , mathematics , linguistics , philosophy , geometry , mathematical analysis
With the advancement of image editing tools in today's world, the manipulation of images like cropping, cloning, resizing, etc., becomes an easy proposition and on the other end, checking or determining whether an image has been manipulated or not, becomes a great challenge. Copy‐move forgery in images is the most popular tampering method in which a portion of an image is copied and pasted in some other location of the same image. The detection of copy‐move forgery has become a prominent research area. This study presents a detailed review and critical discussions with pros and cons of each of copy‐move forgery detection techniques from 2007 to 2017. This study also addresses the variation in databases, issues, challenges, future directions and references in this domain.