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Embed, track and authenticate images online with SDW-WebCrawler
School of Computing and Intelligent Systems, University of Ulster, United Kingdom.
School of Computing and Intelligent Systems, University of Ulster, United Kingdom.
School of Computing and Intelligent Systems, University of Ulster, United Kingdom.
School of Computing and Intelligent Systems, University of Ulster, United Kingdom.
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2011 (English)In: 2011 Irish Machine Vision and Image Processing Conference, IEEE, 2011, p. 76-81Conference paper, Published paper (Refereed)
Abstract [en]

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 TinEye 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. 

Place, publisher, year, edition, pages
IEEE, 2011. p. 76-81
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:umu:diva-206431DOI: 10.1109/IMVIP.2011.22Scopus ID: 2-s2.0-84881000208ISBN: 9780769546292 (electronic)ISBN: 978-1-4673-0230-2 (print)OAI: oai:DiVA.org:umu-206431DiVA, id: diva2:1749278
Conference
2011 15th Irish Machine Vision and Image Processing Conference, IMVIP 2011, Dublin, Ireland, September 7-9, 2011
Available from: 2023-04-06 Created: 2023-04-06 Last updated: 2025-02-07Bibliographically approved

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Cheddad, Abbas

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Umeå Centre for Molecular Medicine (UCMM)
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf