Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/112897
DC FieldValue
dc.titleSelf-alignment in marking edges of man-made objects
dc.contributor.authorYuan, B.
dc.contributor.authorLiew, S.C.
dc.contributor.authorKwoh, L.K.
dc.date.accessioned2014-11-28T07:58:03Z
dc.date.available2014-11-28T07:58:03Z
dc.date.issued2009
dc.identifier.citationYuan, B.,Liew, S.C.,Kwoh, L.K. (2009). Self-alignment in marking edges of man-made objects. 30th Asian Conference on Remote Sensing 2009, ACRS 2009 3 : 1535-1537. ScholarBank@NUS Repository.
dc.identifier.isbn9781615679843
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/112897
dc.description.abstractThe extraction of geometries of man-made objects, such as buildings and roads, from the images of air-borne sensors is the basis for digital city reconstruction. It has enormous benefits to the development of our society. Google Earth, for instance, provides details of cities around the world in 2D and 3D forms with the availability of precise information of man-made structures for anyone with Internet connection. Obtaining such geometric data using air-borne sensors, either semi-or fully automatically, is a very challenging task that inspire much research efforts in recent years. Fully automatic algorithms for extracting geometries of man-made objects is most desirable for real world applications. Due to the limitations of data and algorithms available, the current practical solutions still involve manual operators in key areas such as curvilinear feature identification and extraction. This paper presents some computerized aids to manual operations, such as autom atic alignment along the prominent structural edges on satellite images. These aids can effectively improve the efficiency and accuracy of manual operations. Various approaches are examined by their performances and potential for fully automatic deployment.
dc.sourceScopus
dc.subjectDigital City
dc.subjectFeatures Extraction
dc.subjectMan-made Objects
dc.subjectSatellite Imagery
dc.typeConference Paper
dc.contributor.departmentCTR FOR REM IMAGING,SENSING & PROCESSING
dc.description.sourcetitle30th Asian Conference on Remote Sensing 2009, ACRS 2009
dc.description.volume3
dc.description.page1535-1537
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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