Novel Technique for Real Time Individual Object Sorting

The content of the present paper aims at seeking faster speed and lower cost methods for characterizing granular objects in general, and cereal grains in particular. The approach is based on simultaneous cross-combined optical and impedimetric sensing techniques in the MHz range, applied to flowing streams so as to determine real-time 3D morphological characterization of single objects. The main advantages of the proposed approach rely on the high discriminatory capacity of the object classes and on the high degree of parallelism, capable of processing large amounts of material on production lines. The use of integrated electronic systems also allows high operative speed, easy calibration and flexibility to the required classification features.