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Embed, Track and Authenticate Images Online with SDW-WebCrawler

Yogarajah, P, Condell, J, Curran, K, McKevitt, P and Cheddad, A (2011) Embed, Track and Authenticate Images Online with SDW-WebCrawler. In: Irish Machine Vision and Image Processing Conference (IMVIP-2011), Dublin City University, Dublin, Ireland. IEEE Computer Society. 6 pp. [Conference contribution]

PDF - Accepted Version

URL: http://www.computer.org/csdl/proceedings/imvip/2011/4629/00/4629a076-abs.html

DOI: 10.1109/IMVIP.2011.22


The Internet is a widely open source to everyone to access Web pages. Using a web browser anyone can access websites. Because of this facility people can easily download images from websites without the owner's knowledge and use them in their own documents. Also image content may be modified for illegal purposes. Therefore a system is needed to authenticate images over the Web. Web image authentication is a challenging task that requires web crawlers to track and download images for authentication. Most of the known web image tracking engines such as Tin Eye and PicScout retrieve images according to the image infringement of the original image. However, these systems do not have the facility to authenticate the retrieved image, i.e. whether the retrieved image is similar to the original image or any image content alteration has occurred in the retrieved image and who is the copyrighted owner of the retrieved image. In order to solve the above mentioned drawbacks this paper presents a framework to protect image content, track it over the internet and authenticate the content. The proposed framework is based on self-embedding (i.e. where secret data and a binary version of the image are encrypted and embedded into the image), tracking (i.e. where a web crawler traverses over the internet to download images) and self-authentication (i.e. where the binary version of the hidden data is extracted to authenticate the image). Also another advantage of the proposed system is that it does not need the original image for the authentication process.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Faculty of Arts
Faculty of Arts > School of Creative Arts and Technologies
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:21647
Deposited By: Professor Paul McKevitt
Deposited On:08 May 2012 15:19
Last Modified:09 Dec 2015 11:03

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