A study of image processing on identifying cucumber disease

6Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

This article is free to access.

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. © 2012 IFIP Federation for Information Processing.

Cite

CITATION STYLE

APA

Wei, Y., Chang, R., Wang, Y., Liu, H., Du, Y., Xu, J., & Yang, L. (2012). A study of image processing on identifying cucumber disease. In IFIP Advances in Information and Communication Technology (Vol. 370 AICT, pp. 201–209). https://doi.org/10.1007/978-3-642-27275-2_22

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free