| Grant number: | 13/16452-8 |
| Support Opportunities: | Scholarships in Brazil - Master |
| Start date: | November 01, 2013 |
| End date: | February 28, 2015 |
| Field of knowledge: | Physical Sciences and Mathematics - Geosciences - Geodesy |
| Principal Investigator: | Aluir Porfírio Dal Poz |
| Grantee: | Michelle Sayuri Yano |
| Host Institution: | Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil |
Abstract In this project a methodology is proposed for segmentation of buildings roof surfaces present in LASER scanning data, based on image processing techniques and the RANdom Sample Consensus (RANSAC) method. To avoid the simultaneous seek of roof surfaces in the entire LASER's point cloud, initially will be performed a pre-processing of the point cloud to separate the building regions. The separation of building points will be accomplished by the region's delimitation of each building by detection, vectorization and poligonization of the building's contours. This procedure allows the separate analysis of each building, decreasing significantly the computational effort and avoiding the merging of different building segments accidentally coplanar. Posteriorly, the RANSAC method will be used to identify sets of coplanar points belonging to the roof's faces. This method uses a minimum amount of data to determine a hypothetical model (plans, spheres, cylinders), allowing the posterior extension of the initial data sets based on consistency analysis, until the accomplishment of grouping of data's number that ensure the appropriate performance of the hypothetical model. The RANSAC segmentation can produce fragmented results, which also requires a post-processing to the merger of the planar segments spatially close and parallel. This will be performed determining threshold related to the concept of continuity, which involves the proximity and orientation analysis. | |
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