Building Footprint Extraction from LiDAR Data and Imagery Information
This study presents an automatic method for regularisation of building outlines. Initially, building segments are extracted using a new fusion method. Data- and model-driven approaches are then combined to generate approximate building polygons. The core part of the method includes a novel data-driv...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
Curtin University
2020
|
| Online Access: | http://hdl.handle.net/20.500.11937/79920 |
| _version_ | 1848764128849559552 |
|---|---|
| author | Mousa, Yousif Abdul-kadhim |
| author_facet | Mousa, Yousif Abdul-kadhim |
| author_sort | Mousa, Yousif Abdul-kadhim |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This study presents an automatic method for regularisation of building outlines. Initially, building segments are extracted using a new fusion method. Data- and model-driven approaches are then combined to generate approximate building polygons. The core part of the method includes a novel data-driven algorithm based on likelihood equation derived from the geometrical properties of a building. Finally, the Gauss-Helmert and Gauss-Markov models adjustment are implemented and modified for regularisation of building outlines considering orthogonality constraints. |
| first_indexed | 2025-11-14T11:14:26Z |
| format | Thesis |
| id | curtin-20.500.11937-79920 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:14:26Z |
| publishDate | 2020 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-799202020-07-08T01:39:42Z Building Footprint Extraction from LiDAR Data and Imagery Information Mousa, Yousif Abdul-kadhim This study presents an automatic method for regularisation of building outlines. Initially, building segments are extracted using a new fusion method. Data- and model-driven approaches are then combined to generate approximate building polygons. The core part of the method includes a novel data-driven algorithm based on likelihood equation derived from the geometrical properties of a building. Finally, the Gauss-Helmert and Gauss-Markov models adjustment are implemented and modified for regularisation of building outlines considering orthogonality constraints. 2020 Thesis http://hdl.handle.net/20.500.11937/79920 Curtin University fulltext |
| spellingShingle | Mousa, Yousif Abdul-kadhim Building Footprint Extraction from LiDAR Data and Imagery Information |
| title | Building Footprint Extraction from LiDAR Data and Imagery Information |
| title_full | Building Footprint Extraction from LiDAR Data and Imagery Information |
| title_fullStr | Building Footprint Extraction from LiDAR Data and Imagery Information |
| title_full_unstemmed | Building Footprint Extraction from LiDAR Data and Imagery Information |
| title_short | Building Footprint Extraction from LiDAR Data and Imagery Information |
| title_sort | building footprint extraction from lidar data and imagery information |
| url | http://hdl.handle.net/20.500.11937/79920 |