Open AccessVisual Feature Based Image Forgery Detection
Author(s) -
D. Vaishnavi,
D. Mahalakshmi,
Venkata Siva Rao Alapati
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.6.20436
Subject(s) - computer science , feature (linguistics) , artificial intelligence , computer vision , image (mathematics) , notice , digital image , false positive rate , pattern recognition (psychology) , image processing , law , philosophy , linguistics , political science
In present days, the images are building up in digital form and which may hold essential information. Such images can be voluntarily forged or manipulated using the image processing tools to abuse it. It is very complicated to notice the forgery by naked eyes. In particular, the copy move forgery is enormously demanding one to expose. Hence, this paper put forwards a method to determine the copy move forgery by extracting the visual feature called speed up robust features (SURF). In the direction to quantitatively analyze the performance, the metrics namely false positive rate and true positive rate are estimated and also comparative study is carried out by previous existing methods.