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dc.contributor.authorAwrangjeb, Mohammad
dc.contributor.authorFraser, Clive S
dc.contributor.editorClive S. Fraser, Jeff Walker, Mark L. Williams
dc.date.accessioned2018-03-20T12:30:28Z
dc.date.available2018-03-20T12:30:28Z
dc.date.issued2013
dc.identifier.isbn9781479911141
dc.identifier.issn2153-6996
dc.identifier.doi10.1109/IGARSS.2013.6723079
dc.identifier.urihttp://hdl.handle.net/10072/99603
dc.description.abstractSeparation of buildings from trees is a major challenge in automatic building detection. In residential and hilly areas, buildings are often surrounded by dense vegetation. This paper presents a three-step method for effective separation of buildings from trees. Firstly, height and width thresholds are applied to LIDAR data for removing small bushes and trees with small horizontal coverage, respectively. The generation of the building mask, where each black region indicates a void area from which there are no laser returns below the height threshold, also helps in separation of buildings from the nearby trees. Then image entropy and colour information are applied together to remove trees exhibiting high texture. Finally, an innovative rule-based procedure is employed using the edge orientation histogram from the imagery to eliminate the remaining trees. Experimental results show that the algorithm offers high building detection rate in complex scenes which are hilly and densely vegetated.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeUnited States
dc.relation.ispartofconferencenameIEEE International Geoscience and Remote Sensing Symposium (IGARSS)
dc.relation.ispartofconferencetitle2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
dc.relation.ispartofdatefrom2013-07-21
dc.relation.ispartofdateto2013-07-26
dc.relation.ispartoflocationMelbourne, AUSTRALIA
dc.relation.ispartofpagefrom1533
dc.relation.ispartofpageto1536
dc.subject.fieldofresearchImage Processing
dc.subject.fieldofresearchComputer Vision
dc.subject.fieldofresearchPhotogrammetry and Remote Sensing
dc.subject.fieldofresearchcode080106
dc.subject.fieldofresearchcode080104
dc.subject.fieldofresearchcode090905
dc.titleEffective building detection in complex scenes
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionPost-print
gro.rights.copyright© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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gro.griffith.authorAwrangjeb, Mohammad


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    Contains papers delivered by Griffith authors at national and international conferences.

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