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Proceedings Paper

Statistical estimators of spatial vector fields in defect classification and texture modeling of high-tech surfaces
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Paper Abstract

Especially for wafers, hard disks and flat panel displays fast and accurate technical means for roughness measurement, texture modeling, defect detection and classification are needed. However, speed and accuracy are often contradictory in these fields. It is shown that by using scatter (ARS/BRDF) data a very fast acquisition of surface microtopography information is possible. Furthermore, it is pointed out that the von-Mises-distribution can replace the Gaussian distribution for circular or spherical vector fields, i.e. BRDF data obtained from a variety of technical surfaces by stray light measuring or sensing. For the purpose of in line quality control formulae for the parameters corresponding to mean and variance in Gaussian distributions as well as parameter tests and confidence intervals for circular unimodal vector fields will be given. Finally, measurement and simulation results will be compared to circular statistical inference.

Paper Details

Date Published: 14 October 1997
PDF: 12 pages
Proc. SPIE 3167, Statistical and Stochastic Methods in Image Processing II, (14 October 1997); doi: 10.1117/12.290279
Show Author Affiliations
Hendrik Rothe, Univ. of the Federal Armed Forces (Germany)
Dorothee Hueser, Univ. of the Federal Armed Forces (Germany)

Published in SPIE Proceedings Vol. 3167:
Statistical and Stochastic Methods in Image Processing II
Francoise J. Preteux; Jennifer L. Davidson; Edward R. Dougherty, Editor(s)

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