Rice Grain Shape Identification Method Based On Computer Vision
method of using a computer vision system to replace the human eye in identifying the grain shape of whole grains and broken rice is proposed. A set of rice grain shape recognition device based on computer vision technology is designed. Image processing methods such as grayscale transformation, threshold segmentation, and smoothing are used to obtain the grain shape image of rice. Then the area and perimeter of the rice grain are extracted based on the grain shape characteristics of the rice. 16 characteristic parameters such as length, length, and width are processed using the principal component analysis method. The first three principal components combine all the grain shape characteristic parameters and are used as the input characteristic values of the BP neural network to train and large-scale the network. Rice grain shape identification. The test results show that the accuracy of this method for identifying whole grain rice is 98.67%; the accuracy for identifying broken rice is 92.09%.
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Original research was done by Wan Peng, Sun Yu, Sun Yonghai
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