Premium
Feature‐specific Measurement of Surface Roughness in SEM Images
Author(s) -
Russ John C.,
Russ J. Christian
Publication year - 1987
Publication title -
particle and particle systems characterization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 56
eISSN - 1521-4117
pISSN - 0934-0866
DOI - 10.1002/ppsc.19870040106
Subject(s) - fractal dimension , brightness , feature (linguistics) , texture (cosmology) , surface finish , artificial intelligence , plot (graphics) , pattern recognition (psychology) , fractal , pixel , contrast (vision) , perpendicular , surface roughness , dimension (graph theory) , mathematics , surface (topology) , computer vision , computer science , geometry , statistics , optics , image (mathematics) , materials science , physics , mathematical analysis , linguistics , philosophy , composite material , pure mathematics
Characterization of the roughness of surfaces of individual features present in SEM images is obtained from the slope and intercept of a plot of the brightness difference between pixels as a function of their separation distance, in directions parallel and perpendicular to the scan lines within the outlines of the feature. The descriptive names contrast and texture are given to the intercept and slope of this plot, respectively. These parameters can be used to classify features, just as measures of size, shape, etc. are used for selection, distribution plots and statistical comparison. Evidence is also shown for a correlation between the texture and the fractal dimension of the feature profile, and consequently with the surface fractal dimension of the feature.