F. Ros et al., RECOGNITION OF OVERLAPPING PARTICLES IN GRANULAR PRODUCT IMAGES USINGSTATISTICS AND NEURAL NETWORKS, Food control, 6(1), 1995, pp. 37-43
Image analysis can be used to characterize granular populations in man
y processes in the food industry or in agricultural engineering. Eithe
r global or individual parameters cart be extracted from the image. Ho
wever, granular products may agglomerate on the image, bringing bias m
easurements of individual parmeters: products which agglomerate have t
o be recognized. This is done by a combination of image analysis (to p
re-process and extract features), statistical methods (to reduce infor
mation) and neural network techniques (to take decisions).