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Plastics recovery and recycling represent an important issue. Polyolefins, polyethilene (PE) and polypropylene (PP), recovery from complex waste streams is a challenging issue actually not yet efficiently solved. Furthermore, PP, high density polyethylene (HDPE) and low density polyethylene (LDPE) together are both difficult to separate and chemically incompatible. To produce high-purity granulates from these concentrates, of a quality comparable to materials prodluced from post-industrial waste, mixtures must be accurately sorted, and, to be economically and ecologically sound, most of the polyolefins should end up in a useful product. Such accurate and efficient separations exist, but they involve multiple separations, they are therefore expensive, difficult to control and often do not allow the production of good concentrates. The possibility to develop efficient and low cost recognition logics to control the process and certify the products trough the implementation of on-line HyperSpectral Imaging (HSI) based architectures is presented and evaluated in terms of reliability and robustness of the results.