DocumentCode :
2558673
Title :
A new method of point clouds extraction from the 3D volume data
Author :
Wang, Zhaofeng ; Yan, Bin ; Li, Jianxin ; Tong, Li ; Chen, Jian
Author_Institution :
China Nat. Digital Switching Syst. Eng. & Technol. Res. Center(NDSC), Zhengzhou, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
362
Lastpage :
365
Abstract :
The point clouds is an important kind of three-dimensional data expression form. In the 3D point-based rendering and reverse engineering, it acts as an irreplaceable role. In this paper, the volume data was preprocessed and broken down into a series of 2D slices for contours extraction, finally all of the points extracted were inputted into self-organized network for cluster analysis. The feasibility of this method was proved in both theory and practice. The approach may be taken as a useful reference for researchers working on extracting point clouds from volume data.
Keywords :
feature extraction; pattern clustering; rendering (computer graphics); reverse engineering; self-organising feature maps; solid modelling; 2D slices; 3D point-based rendering; 3D volume data; SOM; cluster analysis; contour extraction; neural network; point clouds extraction; reverse engineering; self-organized mapping; self-organized network; three-dimensional data expression form; Algorithm design and analysis; Computed tomography; Data mining; Neurons; Rendering (computer graphics); Shape; Vectors; Neural Network; Point Clouds Extraction; Self-Organized Mapping(SOM); Volume Data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234642
Filename :
6234642
Link To Document :
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