Two-Dimensional Systematic Point Count for Volume Fraction Analysis from a Poisson Theoretic Approach.

Abstract

In many fields of scientific investigation, the structure of cellular aggregates or random arrays of discrete particles imbedded in some solid is observed on a two-dimensional section and inferences drawn therefrom as to the real structure in three dimensions. A fast, reliable method for the quantitative determination of the percentages of these micro- or macroconstituents would be of great benefit for structural studies in the solid state. One of the techniques most often used for the estimation of volume fractions from measurements made on a random two-dimensional section is that of the two-dimensional systematic point count, i.e., that the fractional number of regularly dispersed points falling within the boundaries of a two-dimensional feature on a plane provides an unbiased estimate of the areal fraction, and consequently of the volume fraction, of that feature. The two-dimensional systematic point count is demonstrated here from a Poisson theoretic approach. In addition, two methods of application are investigated: one using a normal approximation, the other, the Poisson distribution. The relationship between the latter and the point-count precedure is also indicated. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 31, 1971
Accession Number
AD0722333

Entities

People

  • Burton N. Navid
  • James P. Grimes

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Boundaries
  • Geometry
  • Measurement
  • Particles
  • Two Dimensional

Readers

  • Aerosol Science/Aerosol Physics
  • Computer Vision.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms