An inspection method of rice milling degree based on machine vision and gray-gradient co-occurrence matrix

Abstract

A detection method of the rice milling degree was proposed based on machine vision with gray-gradient co-occurrence matrix. Using an experimental mill machine, different milling degree samples of rice were prepared. The rice kernel image of the different milling degree was get by a machine vision detecting system, then the texture features of the rice image were obtained by using gray-gradient co-occurrence matrix, at last the Fisher discriminate functions constructed using stepwise discriminate analysis were used to detect the milling degree of the rice samples. The testing results show that the average accuracy rate of the different milling degree detected using the method of 4 rice samples is 94.00%. © 2011 IFIP International Federation for Information Processing.