Powder Technology, Vol.91, No.3, 217-227, 1997
Particle-Shape Characterization Using Image-Analysis and Neural Networks
An image analysis method is presented which effectively describes the shape of a convex or concave particle. The method uses the Fourier descriptors evaluated from the Fourier series expansion of the angular bend of the periphery of a particle as a function of its are length. The Fourier descriptors are then used as inputs to unsupervised or supervised artificial neural networks to cluster and classify particles according to their shape. A number describing the class of a single particle or the average class of a population of particles can therefore be deduced to characterize them.