An illumination-invariant phase-shifting algorithm for three-dimensional profilometry

2 February 2012 An illumination-invariant phase-shifting algorithm for three-dimensional profilometry

Fuqin Deng, Chang Liu, Wuifung Sze, Jiangwen Deng, Kenneth S. M. Fung, W. H. Leung, Edmund Y. Lam

Author Affiliations +

Proceedings Volume 8300, Image Processing: Machine Vision Applications V; 830005 (2012) https://doi.org/10.1117/12.911113
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Uneven illumination is a common problem in real optical systems for machine vision applications, and it contributes significant errors when using phase-shifting algorithms (PSA) to reconstruct the surface of a moving object. Here, we propose an illumination-reflectivity-focus (IRF) model to characterize this uneven illumination effect on phase-measuring profilometry. With this model, we separate the illumination factor effectively, and then formulate the phase reconstruction as an optimization problem. To simplify the optimization process, we calibrate the uneven illumination distribution beforehand, and then use the calibrated illumination information during surface profilometry. After calibration, the degrees of freedom are reduced. Accordingly, we develop a novel illumination-invariant phase-shifting algorithm (II-PSA) to reconstruct the surface of a moving object under an uneven illumination environment. Experimental results show that the proposed algorithm can improve the reconstruction quality both visually and numerically. Therefore, using this IRF model and the corresponding II-PSA, not only can we handle uneven illumination in a real optical system with a large field of view (FOV), but we also develop a robust and efficient method for reconstructing the surface of a moving object.

Citation Download Citation

Fuqin Deng, Chang Liu, Wuifung Sze, Jiangwen Deng, Kenneth S. M. Fung, W. H. Leung, and Edmund Y. Lam "An illumination-invariant phase-shifting algorithm for three-dimensional profilometry", Proc. SPIE 8300, Image Processing: Machine Vision Applications V, 830005 (2 February 2012); https://doi.org/10.1117/12.911113

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