Imaging techniques for process optmization an control in glass recycling

Glass fragments (cullets) to be recycled present different market values according to their color. Glass recycling plants perform cullets sorting mainly discriminating colored glasses from white and half white glasses; furthermore sorting presents some other technological limits concerning the minimum cullet size, about 45 mm, that is possible to analyze. Cullets which are collected without distinctions of color, can be used primarily for the production of green glass and only in part for the production of yellow glass. The production of white glass requires that only cullets of that color be employed. 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 are analyzed the possibility that could be offered by the adoption of a color imaging based approach to realize cullets sorting, analyzing the textural attributes of the investigated cullets' image field. This study was mainly focused on the effects that cullets surface status and characteristics produce on the detected color-textural characteristics and they can influence the further classification. All the tests have been performed on glass samples as they result after the cleaning stage, impurities removal, of an industrial glass recycling plant.