Accurate surface reconstruction of large 3D objects from range data

Xiaokun Li; Lei He; Bryan Everding; Chia Yung Han; William G. Wee

doi:10.1117/12.477507

22 May 2003 Accurate surface reconstruction of large 3D objects from range data

Xiaokun Li, Lei He, Bryan Everding, Chia Yung Han, William G. Wee

Proceedings Volume 5011, Machine Vision Applications in Industrial Inspection XI; (2003) https://doi.org/10.1117/12.477507
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

An algorithm for 3D surface reconstruction of large objects using a structured light pattern ranging system is presented. Highly accurate industrial inspection applications have been constrained by the limited range resolution and accuracy of current ranging devices and techniques. To overcome the limited range resolution, the ranging sensor uses a small field-of-view and multiple views. The proposed algorithm fuses surface data patches from the views to construct a large object surface. The algorithm also increases the accuracy of the reconstructed object with efficient numerical analysis and pre-processing. Experimental results show that the algorithm and the current sensor setup can reconstruct an object for inspection applications with the accuracy of approximately 1 mil (2.54μm ) tolerance.

Citation Download Citation

Xiaokun Li, Lei He, Bryan Everding, Chia Yung Han, and William G. Wee "Accurate surface reconstruction of large 3D objects from range data", Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); https://doi.org/10.1117/12.477507

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