Copyright infringements on the Internet are a major problem for rights owners. Especially copies with a high visual quality must not be published uncontrolled on free online portals - in the perception of content owners such as TV stations for instance. In the THESEUS Core Technology Cluster (CTC), the Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (HHI) and the Fraunhofer Institute for Computer Graphics Research (IGD) have developed innovative technologies for copyright protection. Perceptual hashing algorithms are used to extract short hash values from the content which allow a robust identification of the same. The identified content can be further analyzed concerning its visual quality and thus its appropriateness for online publishing. For that, automatic quality assessment algorithms are applied. This article describes these two approaches. In addition, the sample application 'Detection of copyright infringements' that combines the two developed technologies is described.
%0 Book Section
%1 NickelZhouEtAl14p101
%A Nickel, Claudia
%A Zhou, Xuebing
%A Liu, Mohan
%A Ndjiki-Nya, Patrick
%B Towards the Internet of Services: The THESEUS Research Program
%C Berlin
%D 2014
%E Wahlster, Wolfgang
%E Grallert, Hans-Joachim
%E Wess, Stefan
%E Friedrich, Hermann
%E Widenka, Thomas
%I Springer
%K v1500 springer paper ai business image video processing recognition optimize secure zzz.th
%P 101-110
%R 10.1007/978-3-319-06755-1_8
%T Content Identification and Quality-Based Ranking
%X Copyright infringements on the Internet are a major problem for rights owners. Especially copies with a high visual quality must not be published uncontrolled on free online portals - in the perception of content owners such as TV stations for instance. In the THESEUS Core Technology Cluster (CTC), the Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (HHI) and the Fraunhofer Institute for Computer Graphics Research (IGD) have developed innovative technologies for copyright protection. Perceptual hashing algorithms are used to extract short hash values from the content which allow a robust identification of the same. The identified content can be further analyzed concerning its visual quality and thus its appropriateness for online publishing. For that, automatic quality assessment algorithms are applied. This article describes these two approaches. In addition, the sample application 'Detection of copyright infringements' that combines the two developed technologies is described.
@incollection{NickelZhouEtAl14p101,
abstract = {Copyright infringements on the Internet are a major problem for rights owners. Especially copies with a high visual quality must not be published uncontrolled on free online portals - in the perception of content owners such as TV stations for instance. In the THESEUS Core Technology Cluster (CTC), the Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (HHI) and the Fraunhofer Institute for Computer Graphics Research (IGD) have developed innovative technologies for copyright protection. Perceptual hashing algorithms are used to extract short hash values from the content which allow a robust identification of the same. The identified content can be further analyzed concerning its visual quality and thus its appropriateness for online publishing. For that, automatic quality assessment algorithms are applied. This article describes these two approaches. In addition, the sample application 'Detection of copyright infringements' that combines the two developed technologies is described.},
added-at = {2015-01-15T08:41:34.000+0100},
address = {Berlin},
author = {Nickel, Claudia and Zhou, Xuebing and Liu, Mohan and Ndjiki-Nya, Patrick},
biburl = {https://www.bibsonomy.org/bibtex/2fc09e5547ecc1c359f8772221720b3f8/flint63},
booktitle = {Towards the Internet of Services: The {THESEUS} Research Program},
crossref = {WahlsterGrallertEtAl2014},
doi = {10.1007/978-3-319-06755-1_8},
editor = {Wahlster, Wolfgang and Grallert, Hans-Joachim and Wess, Stefan and Friedrich, Hermann and Widenka, Thomas},
file = {Springer for Professionals:2014/NickelZhouEtAl14p101.pdf:PDF},
groups = {public},
interhash = {e81ac20e35045dd7ffd9649d9964d78f},
intrahash = {fc09e5547ecc1c359f8772221720b3f8},
keywords = {v1500 springer paper ai business image video processing recognition optimize secure zzz.th},
pages = {101-110},
publisher = {Springer},
timestamp = {2018-04-16T12:03:20.000+0200},
title = {Content Identification and Quality-Based Ranking},
username = {flint63},
year = 2014
}