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dc.contributor.authorDey, Emon Kumar
dc.contributor.authorAwrangjeb, Mohammad
dc.date.accessioned2021-02-16T00:00:55Z
dc.date.available2021-02-16T00:00:55Z
dc.date.issued2020
dc.identifier.issn1939-1404
dc.identifier.doi10.1109/JSTARS.2020.3006258
dc.identifier.urihttp://hdl.handle.net/10072/397435
dc.description.abstractVarious methods for automatic building extraction from remote sensing data including light detection and ranging (LiDAR) data have been proposed over the last two decades but a standard metric for evaluation of the extracted building boundary has not been found yet. An extracted building boundary from LiDAR data usually has a zigzag pattern with missing detail, which makes it hard to compare the boundary with its reference. The existing metrics do not consider the significant point (e.g., corner) correspondences, therefore, cannot identify individual extralap and underlap areas in the extracted boundary. This article proposes an evaluation metric for the extracted boundary based on a newly proposed robust corner correspondence algorithm that finds one-to-one true corner correspondences between the reference and extracted boundaries. Assuming a building has a rectilinear shape, corners and lines are first detected for the extracted boundary. Then, corner correspondences are obtained between the extracted and reference boundaries. Each corner has two corresponding lines on its two sides that ideally are perpendicular to each other. The corner correspondences are finally ranked based on their distance, angle, and parallelism of corresponding lines. The metric is defined as the average minimum distance d_{\mathrm{avg}} from the extracted boundary points to their corresponding reference lines. Extralap and underlap areas are identified by comparing the point distances with d_{\mathrm{avg}}. In experiments, the proposed metric performs more realistic than the existing metrics and finds the individual extralap and underlap areas effectively.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofpagefrom4030
dc.relation.ispartofpageto4043
dc.relation.ispartofjournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
dc.relation.ispartofvolume13
dc.subject.fieldofresearchPhysical Geography and Environmental Geoscience
dc.subject.fieldofresearchArtificial Intelligence and Image Processing
dc.subject.fieldofresearchGeomatic Engineering
dc.subject.fieldofresearchcode0406
dc.subject.fieldofresearchcode0801
dc.subject.fieldofresearchcode0909
dc.subject.keywordsScience & Technology
dc.subject.keywordsPhysical Sciences
dc.subject.keywordsEngineering, Electrical & Electronic
dc.subject.keywordsGeography, Physical
dc.titleA Robust Performance Evaluation Metric for Extracted Building Boundaries From Remote Sensing Data
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationDey, EK; Awrangjeb, M, A Robust Performance Evaluation Metric for Extracted Building Boundaries From Remote Sensing Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13, pp. 4030-4043
dcterms.licensehttp://creativecommons.org/licenses/by/4.0/
dc.date.updated2020-09-14T01:44:50Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© The Author(s) 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorAwrangjeb, Mohammad
gro.griffith.authorDey, Emon Kumar


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