An efficient algorithm for defect reconstruction from 3D point cloud

Chenlei Wei; Zhiyong Zhou; Yakang Dai

doi:10.1117/12.2524243

6 May 2019 An efficient algorithm for defect reconstruction from 3D point cloud

Chenlei Wei, Zhiyong Zhou, Yakang Dai

Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 1106915 (2019) https://doi.org/10.1117/12.2524243
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China

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.

Citation Download Citation

Chenlei Wei, Zhiyong Zhou, and Yakang Dai "An efficient algorithm for defect reconstruction from 3D point cloud", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 1106915 (6 May 2019); https://doi.org/10.1117/12.2524243

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available