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Proceedings Paper

An efficient algorithm for defect reconstruction from 3D point cloud
Author(s): Chenlei Wei; Zhiyong Zhou; Yakang Dai
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Paper Abstract

Defect reconstruction of three-dimensional (3D) surface is a challenging task in various industry applications for its speed and accuracy. This paper puts forward a fast, robust and automatic approach which is capable of defect reconstruction by establishing a defect profile model with RANdom SAmple Consensus (RANSAC) and Iterative Closest Point (ICP) algorithm. The method mainly contains three steps: defect profile establishment, profile optimization and surface reconstruction. Employed with the 3D data obtained by a structured light scanner, we have tested on surface with different types of concave defects, the results show the effectiveness of our new technique in practical applications for defect reconstruction.

Paper Details

Date Published: 6 May 2019
PDF: 6 pages
Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 1106915 (6 May 2019); doi: 10.1117/12.2524243
Show Author Affiliations
Chenlei Wei, Suzhou Institute of Biomedical Engineering and Technology (China)
Xi'an Jiaotong Univ. (China)
Zhiyong Zhou, Suzhou Institute of Biomedical Engineering and Technology (China)
Yakang Dai, Suzhou Institute of Biomedical Engineering and Technology (China)


Published in SPIE Proceedings Vol. 11069:
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
Chunming Li; Hui Yu; Zhigeng Pan; Yifei Pu, Editor(s)

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