Imaging techniques for process optimization and control in glass recycling

Glass recycling plants perform cullets sorting mainly discriminating colored glasses from white and half white glasses. At present, machines for the separation of cullets according to color are not capable of producing an efficient classification of all the different types. In this paper we analyze the possibility that could be offered by the adoption of a color imaging approach to realize cullets sorting, analyzing the textural attributes of the investigated cullets image field. This study is mainly focused on the effects that cullets surface status and characteristics produced on the detected color-textural characteristics, and they can influence the further classification. All the tests have been performed on glass samples, after the cleaning/impurities removal stage, at an industrial glass recycling plant.