A passive technique for image forgery detection using contrast context histogram features Online publication date: Sat, 04-Jul-2015
by D. Vaishnavi; T.S. Subashini
International Journal of Electronic Security and Digital Forensics (IJESDF), Vol. 7, No. 3, 2015
Abstract: The multimedia data such as digital images are essential to expose the evidence. There are numerous, image editing software through which the original images can be intentionally manipulated or forged for mishandling purposes. It is very difficult to discover the forgery by visually analysing it. Specifically, the copy move forgery is extremely challenging to expose the forged region. In this paper, contrast context histogram (CCH) features are used to effectively detect the copy move forgery and k-means clustering algorithm to segregate the key points of copy move forged regions. The disparity map is created using sum of absolute difference to localise these regions. The comparative study was carried out and the performances reveal that the proposed system is better than the existing methods.
Online publication date: Sat, 04-Jul-2015
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 firstname.lastname@example.org