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

Hendrik Rothe; Dorothee Hueser

doi:10.1117/12.290279

14 October 1997 Statistical estimators of spatial vector fields in defect classification and texture modeling of high-tech surfaces

Hendrik Rothe, Dorothee Hueser

Author Affiliations +

Proceedings Volume 3167, Statistical and Stochastic Methods in Image Processing II; (1997) https://doi.org/10.1117/12.290279
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

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.

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Hendrik Rothe and Dorothee Hueser "Statistical estimators of spatial vector fields in defect classification and texture modeling of high-tech surfaces", Proc. SPIE 3167, Statistical and Stochastic Methods in Image Processing II, (14 October 1997); https://doi.org/10.1117/12.290279

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