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

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.

There is no consensus on the minimum number of particles that should be analyzed for determination of particle size distributions and particle shape characterization. Four methodologies for determination of this number for particle size distribution and two for particle shape were tested using particles of guava juice powder and guava juice powder granulated in a fluidized bed.Figure optionsDownload as PowerPoint slideHighlights
► What’s the minimum number of particles (MNP) to be analyzed by image analysis.
► Comparison between different methodologies.
► 550 would be the MNP necessary for determination of the percentage distributions.
► 100 would be the MNP required for determination of the shape descriptors.