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Proceedings Paper

Statistical Analysis Of Random And Pseudo Random Rough Surfaces
Author(s): Monique Rasigni; Georges Rasigni; Francoise Varnier; Christophe Dussert; Jacqueline Palmari; Nicole Mayani; Antoine Llebaria
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Paper Abstract

For many years we have developed a method to reconstruct the profiles of statistically rough surfaces. This method is based on a microdensitometer analysis of electron micrographs of shadowed surface replicas. From the quantized profiles it is possible to compute the statistical moments -particularly the second order one called autocovariance function (ACF)- that characterize the surface. In general ACF's for pseudorandom surfaces are not decreasing monotonic functions and some complications arise when the definition of a auto-covariance length for those surfaces is considered. Solutions are proposed to overcome them; in particular, it seems preferable to deduce certain statistical parameters from the spectrum instead of the ACF. Moreover a new approach based on the minimal spanning tree (MST) -which is a graph constructed on the set of points representing the position of features on a surface- is proposed to study statistically order and disorder in the distribu-tion of these features.

Paper Details

Date Published: 21 March 1989
PDF: 9 pages
Proc. SPIE 1009, Surface Measurement and Characterization, (21 March 1989); doi: 10.1117/12.949157
Show Author Affiliations
Monique Rasigni, Faculte des Sciences St. Jerome (France)
Georges Rasigni, Faculte des Sciences St. Jerome (France)
Francoise Varnier, Faculte des Sciences St. Jerome (France)
Christophe Dussert, Faculte des Sciences St. Jerome (France)
Jacqueline Palmari, Faculte des Sciences St. Jerome (France)
Nicole Mayani, Faculte des Sciences St. Jerome (France)
Antoine Llebaria, Laboratoire d'Astronomie Spatiale (France)


Published in SPIE Proceedings Vol. 1009:
Surface Measurement and Characterization
Jean M. Bennett, Editor(s)

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