A Detection Method of Rice Process Quality Based on the Color and BP Neural Network

Abstract : This paper proposed a detection method of rice process quality using the color and BP neural network. A rice process quality detection device based on computer vision technology was designed to get rice image, a circle of the radius R in the abdomen of the rice was determined as a color feature extraction area, and which was divided into five concentric sub-domains by the average area, the average color of each sub-region H was extraction as the color feature values described in the surface process quality of rice, and then the 5 color feature values as input values were imported to the BP neural network to detection the surface process quality of rice. The results show that the average accuracy of this method is 92.50% when it was used to detect 4 types of rice of different process quality.
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Communication dans un congrès
Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-344 (Part I), pp.25-34, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18333-1_4〉
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Peng Wan, Changjiang Long, Xiaomao Huang. A Detection Method of Rice Process Quality Based on the Color and BP Neural Network. Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-344 (Part I), pp.25-34, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18333-1_4〉. 〈hal-01559632〉

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