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Proceedings Paper

Morphological measurement of surface roughness
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Paper Abstract

Morphological granulometric moments have proven useful for quantification and classification of image texture. This paper considers their use as measures of surface roughness. The analysis is based on simulations in the framework of a modified Boolean random function model for surfaces. Four granulometric features are considered: the pattern-spectrum mean and pattern-spectrum variance for both opening and closing granulometries generated by flat structuring elements. The expectations of these granulometric moments are compared with the expectations of the classical average and root-mean-square roughness across a range of Boolean models.

Paper Details

Date Published: 6 October 1998
PDF: 9 pages
Proc. SPIE 3521, Machine Vision Systems for Inspection and Metrology VII, (6 October 1998); doi: 10.1117/12.326949
Show Author Affiliations
Yoganand Balagurunathan, Texas A&M Univ. (United States)
Edward R. Dougherty, Texas A&M Univ. (United States)


Published in SPIE Proceedings Vol. 3521:
Machine Vision Systems for Inspection and Metrology VII
Bruce G. Batchelor; John W. V. Miller; Susan Snell Solomon, Editor(s)

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