This study investigates how a statistical filter affects the quality of point cloud segmentation using a Difference of Normals (DoN) multiscale segmentation approach. A system of DoN segmentation combined with a statistical filter was implemented with the help of an open-source Point Cloud Library (PCL) and evaluated on a publicly available dataset containing large point clouds with labeled ground truth objects. The results shows that when a small number of points is filtered results in an improvement of segmentation quality whereas a large number of filtered points decreases segmentation quality. In conclusion, the statistical filter can be combined with DoN segmentation to achieve segmentations of high quality however, non carefully selected thresholds for the statistical filter decreases segmentation quality drastically.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-198060 |
| Date | January 2022 |
| Creators | Fahlstedt, Elof |
| Publisher | Umeå universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UMNAD ; 1360 |
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