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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© 2012 IFIP International Federation for Information Processing
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Wei, Y. et al. (2012). A Study of Image Processing on Identifying Cucumber Disease. In: Li, D., Chen, Y. (eds) Computer and Computing Technologies in Agriculture V. CCTA 2011. IFIP Advances in Information and Communication Technology, vol 370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27275-2_22
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DOI: https://doi.org/10.1007/978-3-642-27275-2_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27274-5
Online ISBN: 978-3-642-27275-2
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