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dc.contributor.authorLovell, Nathan
dc.date.accessioned2017-05-03T17:00:24Z
dc.date.available2017-05-03T17:00:24Z
dc.date.issued2006
dc.date.modified2010-08-30T07:03:50Z
dc.identifier.issn03029743
dc.identifier.doi10.1007/11780519_34
dc.identifier.urihttp://hdl.handle.net/10072/27331
dc.description.abstractObject recognition under uncontrolled illumination conditions remains one of hardest problems in machine vision. Under known lighting parameters, it is a simple task to calculate a transformation that maps sensed values to the expected colors in objects (and minimize the problems of reflections and/or texture). However, RoboCup aims to develop vision systems for natural lighting conditions in which the conditions are not only unknown but also dynamic. This makes fixed color-based image segmentation infeasible. We present a method for color determination under varying illumination conditions that succeeds in tracking the objects of interest in the RoboCup legged league.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom384
dc.relation.ispartofpageto395
dc.relation.ispartofissue20
dc.relation.ispartofjournalLecture Notes in Computer science
dc.relation.ispartofvolume40
dc.rights.retentionY
dc.subject.fieldofresearchMulti-Disciplinary
dc.subject.fieldofresearchcode999999
dc.titleIllumination independent object recognition
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.date.issued2006
gro.hasfulltextNo Full Text
gro.griffith.authorLovell, Nathan H.


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    Contains articles published by Griffith authors in scholarly journals.

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