A Study of Image Processing on Identifying Cucumber Disease

Abstract : Plant disease has been a major constraining factor in the production of cucumber, the traditional diagnostic methods usually take a long time, and the control period is often missed. We take computer image processing as a method, preprocessing the images of more than 100 sheets of collected samples of cucumber leaves, using the region growing method to extract scab area of leaves to get three feature parameters of shape, color and texture. And then, through the establishment of BP neural network pattern, the model identification accuracy of cucumber leaf disease can reach 80%. The experiment shows that by using this method, the diseases of cucumber leaves can be identified more quickly and accurately. And the feature extraction and automatic diagnosis of cucumber leaf disease can be achieved.
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Communication dans un congrès
Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.201-209, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_22〉
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Yong Wei, Ruokui Chang, Yuanhong Wang, Hua Liu, Yanhong Du, et al.. A Study of Image Processing on Identifying Cucumber Disease. Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.201-209, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_22〉. 〈hal-01361139〉

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