<div class="csl-bib-body">
<div class="csl-entry">Stöttinger, J. (2007). <i>Local colour features for image retrieval</i> [Master Thesis, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-19295</div>
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In image retrieval scenarios, many methods use interest point detection at an early stage to find regions in which descriptors are calculated. Finding salient locations in image data is crucial for these tasks. Observing that most current methods use only the luminance information of the images, we investigate the use of colour information in interest point detection. Based on the Harris corner detector, a way to use multi-channel images is explored and different colour spaces are evaluated. To determine the characteristic scale of an interest point, a new colour scale selection method is presented. We show that using colour information and boosting salient colours results in improved performance in retrieval tasks. Large scale image retrieval experiments are carried out to show the gain in retrieval rates under varying circumstances.
de
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
Bildererkennung - Farbraum - Bildklassifizierung - Lokale Deskriptoren
de
dc.subject
Image Retrieval - Interest Points - Local Features - Local Descriptors - Colour Space - Corner Detecion - Object Classification
en
dc.title
Local colour features for image retrieval
en
dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Julian Stöttinger
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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tuw.publication.orgunit
E183 - Institut für Rechnergestützte Automation (Automatisierungssysteme. Mustererkennung)