Abstract: Chalk degree is one of the four important criteria for judgment of rice quality according to China National Standard of Rice. It has been determined by human inspection exclusively so far. A new method was developed to identify chalk and to grade chalk degree of rice using genetic algorithm and neural network in conjunction with computer vision. Genetic neural network was trained to identify chalk pixels and other pixels of endosperm and subsequently to evaluate chalk degree of rice. Two different kinds of rice bought on market were tested to evaluate system performance. Compared experiment results of new method using genetic neural network with that of human inspection, the error rate was less than 0.05. This method is proved to be robust and consistent. It paves the way for on-line automated judgment of chalk degree of rice.