Genetic algorithm based image approximation with geometrical shapes

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URI
http://hdl.handle.net/20.500.14044/37550
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Abstract
In this paper the design parameters of a genetic algorithm (GA) based image approximation / compression algorithm are analyzed. The efficiency using different approximation shapes and with different GA parameters (population size, mutation rate) are evaluated using test runs. Recommended parameter sets for different scenarios are provided.
Title
Genetic algorithm based image approximation with geometrical shapes
xmlui.dri2xhtml.METS-1.0.item-description-titlenumber
18.
Author
Vakulya, Gergely
xmlui.dri2xhtml.METS-1.0.item-contributor-editor
Petőné Csuka, Ildikó
Simon, Gyula
xmlui.dri2xhtml.METS-1.0.item-date-issued
2022
xmlui.dri2xhtml.METS-1.0.item-rights-access
Open access
xmlui.dri2xhtml.METS-1.0.item-other-conferenceTitle
PROCEEDINGS of 17th International Symposium on Applied Informatics and Related Areas
xmlui.dri2xhtml.METS-1.0.item-other-conferenceDate
2022. November 17.
xmlui.dri2xhtml.METS-1.0.item-language
en
xmlui.dri2xhtml.METS-1.0.item-format-page
4 p.
xmlui.dri2xhtml.METS-1.0.item-subject-oszkar
genetic algorithm, image approximation, geometrical shapes, economic applications
xmlui.dri2xhtml.METS-1.0.item-description-version
Kiadói változat
xmlui.dri2xhtml.METS-1.0.item-other-containerTitle
AIS 2022 – 17th International Symposium on Applied Informatics and Related Areas
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalYear
2022
xmlui.dri2xhtml.METS-1.0.item-other-containerIdentifierIsbn
978-963-449-302-0
xmlui.dri2xhtml.METS-1.0.item-type-type
Konferenciaközlemény
xmlui.dri2xhtml.METS-1.0.item-subject-area
Műszaki tudományok - gépészeti tudományok
xmlui.dri2xhtml.METS-1.0.item-publisher-university
Óbudai Egyetem
xmlui.dri2xhtml.METS-1.0.item-publisher-faculty
Alba Regia Műszaki Kar