[en] shape analysis ; Robustness ; Digital representation
[en] The growing success of image analysis based instruments for particle characterization demonstrates the importance of size and shape analysis in operations involving particulate materials. ISO norms for particle sizing using image analysis are being elaborated to clarify nomenclature and measurement principles. But despite this, there is still a lack of understanding of how the digital representation of a particle affects different size and shape parameters. It is the purpose of this paper to explore the magnitude of estimation errors of a series of size and shape parameters from different digital image representations of a single particle. These images are simulated from grey level images of black particles presenting a Gaussian transition towards their white background. Particles themselves are generated from analytical functions sampled by digital grids with variable densities, positions and orientations. Results of inscribed disk, elongation, circularity, roughness, roundness, etc. are plotted as a function of grid density (magnification) with error bars corresponding to the scattering of results for variable thresholds, grid translations and rotations As a conclusion, confidence intervals are given for parameters as a function of magnification and the most sensitive and robust methods of shape analysis are put forward.