DocumentCode :
2510443
Title :
Image-based approach to generation of offset curves from point cloud
Author :
Zhang Yingjie ; Ge Liling
Author_Institution :
Sch. of Mech. Eng., Xi´an Jiaotong Univ., Xi´an, China
fYear :
2009
fDate :
11-13 June 2009
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, an image-based approach for the generation of offset curves from point cloud is presented. The offset curves/surfaces can be applied to refine the prototype produced by using the rapid prototype method to remedy the potential low precise problem. To reduce the computational complexion, in the approach, the cloud data is segmented into a number of layers by slicing the point cloud along a user-specified direction, i.e. machining direction. The data points in each layer are projected onto a plane that is perpendicular to the machining direction. Furthermore, the data points on the place are transformed into grey-level values on a two dimensional space based on the distance away from the plane. After that, the offset curves can be directly computed by using the linear diffusion-based segmentation method. Although a perfect result hasn´t be achieved, the numerical experimental result shows that the proposed approach is more prospective than the existing ones. One of most advantages is more efficiency and with much less computational cost.
Keywords :
computational complexity; image segmentation; cloud data segmentation; computational complexion; grey-level values; image-based approach; linear diffusion-based segmentation method; machining direction; offset curve generation; point cloud; point cloud slicing; rapid prototype method; two-dimensional space; user-specified direction; Application software; Computational efficiency; Computer aided manufacturing; Computer displays; Image generation; Machining; Materials science and technology; Prototypes; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Type :
conf
DOI :
10.1109/ICBBE.2009.5162923
Filename :
5162923
Link To Document :
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