A comparative analysis of copy-move forgery detection algorithms Online publication date: Wed, 26-Oct-2022
by Mohassin Ahmad; Farida Khursheed
International Journal of Electronic Security and Digital Forensics (IJESDF), Vol. 14, No. 6, 2022
Abstract: Copy-paste/copy-move image forgery is also known as image cloning, in which a portion of an image or entity is copied and pasted to another region of a certain picture. This category of image manipulation has the intent either to conceal the entity or to fabricate the image details. Thus, the authenticity of the photographs in different real-world implementations becomes challenging. The number of cases of image tampering is raising with the simple accessibility of image manipulation tools. Therefore, robust, precise and effective approaches to digital image forgery detection are increasingly required. A study on copy-move forgery detection (CMFD) is performed in this paper using three common schemes and their efficiency is checked and compared on images with rotation and scaling in the copied region. First, we will cover DCT-based CMFD, then adaptive over-segmentation and matching feature point. Finally, CMFD, based on PatchMatch, is addressed. The findings show the very good performance of each system.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Electronic Security and Digital Forensics (IJESDF):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook