The quality of rice includes internal and external appearance. The appearance quality mainly includes chalkiness, chalky grain rate, yellow grain and grain type. At present, the appearance quality of rice remains at the level of artificial visual inspection, which is not only poor in objectivity and repeatability, but also time-consuming and labor-intensive to operate, and has low detection accuracy. The introduction of machine vision (also known as computer vision) technology into the appearance quality parameters of rice is one of the effective ways to achieve rapid rice detection. The appearance of rice appearance quality detector in the modern detection of rice quality is worth recommending.
In the research of rice appearance quality detectors, foreign countries started earlier. At present, there are commercialized instruments and automatic grain quality analyzers. However, these instruments are more expensive and are not suitable for China's national conditions. In China, the research on rice quality testing is still in its infancy, and it mainly stays in the research of detection algorithms. So far, there are no commercially available testing instruments in China.
Through the analysis of the appearance quality meter of rice, it was found that the effective discrimination of chalky rice is the basis for the detection of chalkiness and chalky grain rate. This system uses the method based on artificial neural network to distinguish chalkiness rice. The neural network has distributed storage information and parallel processing. The processing of information has the ability of self-organization and self-learning, which relaxes the constraints required by traditional image recognition methods and can achieve better recognition results. The system uses a three-layer BP network, and the input parameters select chalky size and fractal dimension, which represent the cumulative and distribution information of grayscale in the chalky area respectively; the output parameter is 0 or 1, which represents standard rice and chalky rice respectively. The device has good extensibility, no need to change the system hardware, as long as the method of expanding the system software, you can increase the detection of other appearance quality parameters of rice, such as different varieties of grain, color.
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