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Proceedings Paper

An elliptic phase-shift algorithm for high speed three-dimensional profilometry
Author(s): Fuqin Deng; Zhao Li; Jia Chen; Jiangwen Deng; Kenneth S. M. Fung; Edmund Y. Lam
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Paper Abstract

A high throughput is often required in many machine vision systems, especially on the assembly line in the semiconductor industry. To develop a non-contact three-dimensional dense surface reconstruction system for real-time surface inspection and metrology applications, in this work, we project sinusoidal patterns onto the inspected objects and propose a high speed phase-shift algorithm. First, we use an illumination-reflectivity-focus (IRF) model to investigate the factors in image formation for phase-measuring profilometry. Second, by visualizing and analyzing the characteristic intensity locus projected onto the intensity space, we build a two-dimensional phase map to store the phase information for each point in the intensity space. Third, we develop an efficient elliptic phase-shift algorithm (E-PSA) for high speed surface profilometry. In this method, instead of calculating the time-consuming inverse trigonometric function, we only need to normalize the measured image intensities and then index the built two-dimensional phase map during real-time phase reconstruction. Finally, experimental results show that it is about two times faster than conventional phase-shift algorithm.

Paper Details

Date Published: 6 March 2013
PDF: 8 pages
Proc. SPIE 8661, Image Processing: Machine Vision Applications VI, 86610S (6 March 2013); doi: 10.1117/12.2001417
Show Author Affiliations
Fuqin Deng, The Univ. of Hong Kong (Hong Kong, China)
ASM Pacific Technology Ltd. (Hong Kong, China)
Zhao Li, Istituto Italiano di Tecnologia (Italy)
Jia Chen, Harbin Institute of Technology (China)
Jiangwen Deng, ASM Pacific Technology Ltd. (Hong Kong, China)
Kenneth S. M. Fung, ASM Pacific Technology Ltd. (Hong Kong, China)
Edmund Y. Lam, The Univ. of Hong Kong (Hong Kong, China)


Published in SPIE Proceedings Vol. 8661:
Image Processing: Machine Vision Applications VI
Philip R. Bingham; Edmund Y. Lam, Editor(s)

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