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dc.contributor.authorAwrangjeb, Mohammad
dc.contributor.authorRavanbakhsh, Mehdi
dc.contributor.authorFraser, Clive S
dc.contributor.editorPaparoditis, N
dc.contributor.editorPierrotDeseilligny, M
dc.contributor.editorMallet, E
dc.contributor.editorTournaire, O
dc.date.accessioned2020-03-03T05:05:14Z
dc.date.available2020-03-03T05:05:14Z
dc.date.issued2010
dc.identifier.issn2194-9034
dc.identifier.urihttp://hdl.handle.net/10072/392082
dc.description.abstractThis paper presents an automatic system for the detection of buildings from LIDAR data and multispectral imagery, which employs a threshold-free evaluation system that does not involve any thresholds based on human choice. Two binary masks are obtained from the LIDAR data: a ‘primary building mask’ and a ‘secondary building mask’. Line segments are extracted from around the primary building mask, the segments around trees being removed using the normalized difference vegetation index derived from orthorectified multispectral images. Initial building positions are obtained based on the remaining line segments. The complete buildings are detected from their initial positions using the two masks and multispectral images in the YIQ colour system. The proposed threshold-free evaluation system makes one-to-one correspondences using nearest centre distances between detected and reference buildings. A total of 15 indices are used to indicate object-based, pixel-based and geometric accuracy of the detected buildings. It is experimentally shown that the proposed technique can successfully detect rectilinear buildings, when assessed in terms of these indices including completeness, correctness and quality.
dc.languageEnglish
dc.publisherInternational Society of Photogrammetry and Remote Sensing (ISPRS)
dc.publisher.urihttps://www.isprs.org/proceedings/XXXVIII/part3/a/default.aspx
dc.relation.ispartofconferencenameISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis (PCV)
dc.relation.ispartofconferencetitlePCV 2010 - Photogrammetric Computer Vision and Image Analysis
dc.relation.ispartofdatefrom2010-09-01
dc.relation.ispartofdateto2010-09-03
dc.relation.ispartoflocationSaint Mande, France
dc.relation.ispartofpagefrom49
dc.relation.ispartofpageto54
dc.relation.ispartofissuePart 3A
dc.relation.ispartofvolume38
dc.subject.fieldofresearchGeomatic engineering
dc.subject.fieldofresearchcode4013
dc.subject.keywordsScience & Technology
dc.subject.keywordsComputer Science, Artificial Intelligence
dc.subject.keywordsRemote Sensing
dc.subject.keywordsImaging Science & Photographic Technology
dc.titleBuilding Detection from Multispectral Imagery and LIDAR Data Employing A Threshold-Free Evaluation System
dc.typeConference output
dcterms.bibliographicCitationAwrangjeb, M; Ravanbakhsh, M; Fraser, CS, Building Detection from Multispectral Imagery and LIDAR Data Employing A Threshold-Free Evaluation System, PCV 2010 - Photogrammetric Computer Vision and Image Analysis, 38, pp. 49-54
dcterms.licensehttps://creativecommons.org/licenses/by/3.0/
dc.date.updated2020-02-28T05:42:42Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2010. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorAwrangjeb, Mohammad


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