NDLI: On-line point cloud data extraction algorithm for spatial scanning measurement of irregular surface in copying manufacture

Content Provider	Springer Nature Link
Author	Tao, Ye Li, Yan Wang, Yong Qing Ma, Yu Yong
Copyright Year	2016
Abstract	For obtaining high-quality point cloud data of a measured surface in copying manufacture, 3D scanning devices typically have extremely high data sampling rate to produce huge amounts of dense points, which lead to significant computational challenges for subsequent data processing tasks in practical applications. Bottlenecks are created owing to inefficiencies in storing, manipulating, and transferring the massive point data. On-line point cloud data extraction is an effective means to solve the above problems. This paper proposes a novel on-line point cloud data extraction algorithm for spatial scanning measurement of irregular surface. The proposed data extraction framework can handle point sets of arbitrary and varying size, point density, and scanning line shape. Furthermore, it can reduce extremely dense point cloud data in ensuring data accuracy during the real-time scanning measuring process. Additionally, we present a bi-Akima method for connecting spatial point sequence in non-planar cross section. It is designed to deal with point cloud data extraction for any kinds of scanning lines during the real-time measuring process. Finally, a series of simulations and real measuring experiments are conducted, and the results show a strong data extraction performance of our proposed method both in data reduction ratio and accuracy.
Starting Page	1891
Ending Page	1905
Page Count	15
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	87
Issue Number	5-8
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2016-03-12
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Point cloud data Data extraction Scanning measurement Copying manufacture Bi-Akima method Industrial and Production Engineering Production Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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