The people regard food as the heaven. Rice is a very special commodity. It cannot be separated from three meals a day. The quality of rice has never been overlooked since ancient times, and it is not excessive to describe Taishan as its quality. With the development of the food storage and processing industry and the improvement of people's living standards, people's demand for rice ranges from eating to eating, eating well to eating healthy and nutritious. The quality of rice grader will directly affect the health and safety of people. Therefore, the quality and technical supervision departments at all levels attach great importance and people's attention.

Qualitative rice grader of milled rice grains was carried out in this study using a machine vision system combined with some metaheuristic classification approaches. Images of four different classes of milled rice including Low-processed sound grains (LPS), Low-processed broken grains (LPB), High-processed sound grains (HPS), and High-processed broken grains (HPB), representing quality grades of the product, were acquired using a computer vision system. Four different metaheuristic classification techniques including artificial neural networks, support vector machines, decision trees and Bayesian Networks were utilized to classify milled rice samples. Results of validation process indicated that artificial neural network with 12-5*4 topology had the highest classification accuracy (98.72 %). Next, support vector machine with Universal Pearson VII kernel function (98.48 %), decision tree with REP algorithm (97.50 %), and Bayesian Network with Hill Climber search algorithm (96.89 %) had the higher accuracy, respectively. Results presented in this paper can be utilized for developing an efficient system for fully automated classification and sorting of milled rice grains.

The configuration of the whitening screen did not affect much the characteristics of the rice whitener although the hexagonal screen exhibited a relatively higher performance compared with the rest. Also, the angle of slit has no significant effect over the characteristics of this whitener.

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