Abstract
This paper dealt with the data-processing procedure for detecting justifiable asperity summits from surface topography data and proposed a quantitative assessment of their spatial distribution. The smoothing and differentiation technique was applied to seeking for one local summit within an assessment area. The assessment area was introduced by the use of autocorrelation function on the related surface. As an auxiliary assessment of surface topography, the smoothed slope in the three-dimensions was also defined on the assessment area. Little variation in the slope parameters was found in the case of more than five sampling points for one side of the assessment area. The spatial distribution of the detected summits was characterized both in the vertical and lateral directions. The summit height distribution was assessed by the bias and standard deviation. For the latter direction, a dispersion index composed of the areal density of summits and the mean nearest-distance among summits was presented.
