Open AccessReview, analysis and parameterisation of techniques for copy–move forgery detection in digital images
Author(s) -
Dixit Rahul,
Naskar Ruchira
Publication year - 2017
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.2016.0322
Subject(s) - computer science , digital image , benchmark (surveying) , digital forensics , image (mathematics) , artificial intelligence , computer vision , set (abstract data type) , digital imaging , state (computer science) , digital image processing , image manipulation , pattern recognition (psychology) , image processing , computer security , geography , algorithm , cartography , programming language
Copy–move forgery is one of the most preliminary and prevalent forms of modification attack on digital images. In this form of forgery, region(s) of an image is(are) copied and pasted onto itself, and subsequently the forged image is processed appropriately to hide the effects of forgery. State‐of‐the‐art copy–move forgery detection techniques for digital images are primarily motivated toward finding duplicate regions in an image. The last decade has seen lot of research advancement in the area of digital image forensics, whereby the investigation for possible forgeries is solely based on post‐processing of images. In this study, the authors present a three‐way classification of state‐of‐the‐art digital forensic techniques, along with a complete survey of their operating principles. In addition, they analyse the schemes and evaluate and compare their performances in terms of a proposed set of parameters, which may be used as a standard benchmark for evaluating the efficiency of any general copy–move forgery detection technique for digital images. The comparison results provided by them would help a user to select the most optimal forgery detection technique, depending on the author requirements.