CHARACTERIZATION OF MILL PRODUCTS BY ANALYSIS OF IN-FLOW DIGITALIZED IMAGES

A sensor has been designed and tested in a pilot mill to characterize granular products in the food industry. It consists of: a mechanical s ystem which takes a representative part of the product a CCD camera to capture images, a software package for image analysis and data proces sing. The method consists of comparing a sample with a predetermined ' quality class'. The decision system is built on example learning: real cases fed into the system allow its configuration. Three qualify clas ses have been defined, they correspond to the rolls gap (0.30, 0.40, 0 .50 mm) of the first break rolls of a semolina pilot mill. In these co nditions, the classification accuracy rate achieved by the system is h igher than 80%.