JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
A Point Clouds Fast Thinning Algorithm Based on Sample Point Spatial Neighborhood |
| 영문제목(English Title) |
A Point Clouds Fast Thinning Algorithm Based on Sample Point Spatial Neighborhood |
| 저자(Author) |
Jiaxing Wei
Maolin Xu
Hongling Xiu
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| 원문수록처(Citation) |
VOL 16 NO. 03 PP. 0688 ~ 0698 (2020. 06) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Point clouds have ability to express the spatial entities, however, the point clouds redundancy always involves some uncertainties in computer recognition and model construction. Therefore, point clouds thinning is an indispensable step in point clouds model reconstruction and other applications. To overcome the shortcomings of complex classification index and long time consuming in existing point clouds thinning algorithms, this paper proposes a point clouds fast thinning algorithm. Specifically, the two-dimensional index is established in plane linear array (x, y) for the scanned point clouds, and the thresholds of adjacent point distance difference and height difference are employed to further delete or retain the selected sample point. Sequentially, the index of sample point is traversed forwardly and backwardly until the process of point clouds thinning is completed. The results suggest that the proposed new algorithm can be applied to different targets when the thresholds are built in advance. Besides, the new method also performs superiority in time consuming, modelling accuracy and feature retention by comparing with octree thinning algorithm.
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| 키워드(Keyword) |
Fast Thinning Algorithm
Model Deviation
Point Clouds Thinning
Octree Thinning Algorithm
Thinning Rate
Visualization
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