Image analysis: Statistical study of particle size distribution and shape characterization

Abstract

Image analysis can serve as a fast and convenient approach for the analysis of particle size and shape. However, there is no consensus as to the minimum number of particles required for such analysis and the statistical methodology to be used in its evaluation. Four methodologies for determination of this minimum number for particle size distribution analysis and two for that of particle shape were tested using particles of guava juice powder and guava juice powder granulated in a fluidized bed. The Chi-Square test proved to be a robust and efficient mean for determination of particle size distribution and particle shape characterization. 550 particles was found to be the minimum number of particles necessary for the determination of the particle size distributions, with 100 particles required for determination of the shape descriptors for this specific material.