Automatic classification of grains via pattern recognition techniques

摘要

During production, storage and shipment, a crop of feed grain is often contaminated with admixtures of other grains or foreign material. Failure to meet the contractural limits of purity can result in monetary penalties or may prevent completion of the sales transaction. Presently, purity is established by human inspectors. They subject a carefully selected sample to 100 per cent visual inspection.This paper describes part of the development of a high speed, automatic sorting and grading procedure. A recursive learning pattern classification scheme is described which yields an overall accuracy of about 98 per cent.