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dc.contributor.authorJomier, Genevieve
dc.contributor.authorManouvrier, MAUDE
dc.contributor.authorRukoz, Marta
dc.date.accessioned2009-07-16T10:09:58Z
dc.date.available2009-07-16T10:09:58Z
dc.date.issued2005
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/1168
dc.language.isoenen
dc.subjectcontent-based image retrieval
dc.subjectimage storage
dc.subjectquad-tree
dc.subject.ddc005.7en
dc.titleQuadtree-Based Image Representation and Retrieval
dc.typeChapitre d'ouvrage
dc.description.abstractenThis chapter is a survey of quadtree uses in the image domain from image representation, to image storage and content-based retrieval. A quadtree is a spatial data structure built by a recursive decomposition of space into quadrants. Applied to images, it allows representing image content, compacting or compressing image information, and querying images. For thirteen years, numerous image-based approaches have used this structure. In this chapter, the authors want to underline the contribution of quadtree in image applications.
dc.identifier.citationpages81-106
dc.relation.ispartoftitleSpatial Databases: Technologies, Techniques and Trend
dc.relation.ispartofeditorVassilakopoulos, M.
dc.relation.ispartofpublnameIGI Global
dc.relation.ispartofpublcityHershey (Penn.)
dc.relation.ispartofdate2005
dc.description.sponsorshipprivateouien
dc.subject.ddclabelOrganisation des donnéesen
dc.relation.ispartofisbn978-1591403876
dc.identifier.doi10.4018/978-1-59140-387-6.ch004
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2019-03-26T14:34:00Z
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