{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/12108"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/12108","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Reconstruction of industrial piping installations from laser point clouds using profiling techniques","abstract":"As-built models of industrial piping installations are essential for planning applications in industry. Laser scanning has emerged as the preferred data acquisition method of as built information for creating these three dimensional (3D) models. The product of the scanning process is a cloud of points representing scanned surfaces. From this point cloud, 3D models of the surfaces are reconstructed. Most surfaces are of piping elements e.g. straight pipes, t-junctions, elbows, spheres. The automatic detection of these piping elements in point clouds has the greatest impact on the reconstructed model. Various algorithms have been proposed for detecting piping elements in point clouds. However, most algorithms detect cylinders (straight pipes) and planes which make up a small percentage of piping elements found in industrial installations. In addition, these algorithms do not allow for deformation detection in pipes. Therefore, the work in this research is aimed at the detection of piping elements (straight pipes, elbows, t-junctions and flange) in point clouds including deformation detection.","abstract_html":"As-built models of industrial piping installations are essential for planning applications in industry. Laser scanning has emerged as the preferred data acquisition method of as built information for creating these three dimensional (3D) models. The product of the scanning process is a cloud of points representing scanned surfaces. From this point cloud, 3D models of the surfaces are reconstructed. Most surfaces are of piping elements e.g. straight pipes, t-junctions, elbows, spheres. The automatic detection of these piping elements in point clouds has the greatest impact on the reconstructed model. Various algorithms have been proposed for detecting piping elements in point clouds. However, most algorithms detect cylinders (straight pipes) and planes which make up a small percentage of piping elements found in industrial installations. In addition, these algorithms do not allow for deformation detection in pipes. Therefore, the work in this research is aimed at the detection of piping elements (straight pipes, elbows, t-junctions and flange) in point clouds including deformation detection.","abstract_has_math":false,"creators":["Mapurisa, Willard T"],"institution":"Division of Geomatics","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Sithole, George"],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009","date_published":"2009","updated_at":"2026-07-22T22:23:35Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/12108","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Sithole, George"]},{"key":"dc:creator","label":"Author","values":["Mapurisa, Willard T"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-01-13T03:47:52Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-01-13T03:47:52Z"]},{"key":"dc:date.issued","label":"Date","values":["2009"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Division of Geomatics"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/12108"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes abstract.","Includes bibliographical references (leaves 143-152)."]},{"key":"dc:description.abstract","label":"Abstract","values":["As-built models of industrial piping installations are essential for planning applications in industry. Laser scanning has emerged as the preferred data acquisition method of as built information for creating these three dimensional (3D) models. The product of the scanning process is a cloud of points representing scanned surfaces. From this point cloud, 3D models of the surfaces are reconstructed. Most surfaces are of piping elements e.g. straight pipes, t-junctions, elbows, spheres. The automatic detection of these piping elements in point clouds has the greatest impact on the reconstructed model. Various algorithms have been proposed for detecting piping elements in point clouds. However, most algorithms detect cylinders (straight pipes) and planes which make up a small percentage of piping elements found in industrial installations. In addition, these algorithms do not allow for deformation detection in pipes. Therefore, the work in this research is aimed at the detection of piping elements (straight pipes, elbows, t-junctions and flange) in point clouds including deformation detection."]},{"key":"dc:title","label":"Title","values":["Reconstruction of industrial piping installations from laser point clouds using profiling techniques"]}]}],"canonical_facts":{"dc:contributor.advisor":["Sithole, George"],"dc:creator":["Mapurisa, Willard T"],"dc:date.accessioned":["2015-01-13T03:47:52Z"],"dc:date.available":["2015-01-13T03:47:52Z"],"dc:date.issued":["2009"],"dc:description":["Includes abstract.","Includes bibliographical references (leaves 143-152)."],"dc:description.abstract":["As-built models of industrial piping installations are essential for planning applications in industry. Laser scanning has emerged as the preferred data acquisition method of as built information for creating these three dimensional (3D) models. The product of the scanning process is a cloud of points representing scanned surfaces. From this point cloud, 3D models of the surfaces are reconstructed. Most surfaces are of piping elements e.g. straight pipes, t-junctions, elbows, spheres. The automatic detection of these piping elements in point clouds has the greatest impact on the reconstructed model. Various algorithms have been proposed for detecting piping elements in point clouds. However, most algorithms detect cylinders (straight pipes) and planes which make up a small percentage of piping elements found in industrial installations. In addition, these algorithms do not allow for deformation detection in pipes. Therefore, the work in this research is aimed at the detection of piping elements (straight pipes, elbows, t-junctions and flange) in point clouds including deformation detection."],"dc:identifier.uri":["http://hdl.handle.net/11427/12108"],"dc:language.iso":["eng"],"dc:publisher.department":["Division of Geomatics"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["Reconstruction of industrial piping installations from laser point clouds using profiling techniques"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:23:35Z"}