The Disease Assessment of Cucumber Downy Mildew Based on Image Processing

Cucumber downy mildew is a kind of disease which spreads very fast and isdangerous, in order to prevent the disease, peoplealways spray plenty of pesticides indiscriminately. Accurate assessment of the level of cucumber downy mildew is very important to the disease prevention and control. In a cucum...

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Bibliographic Details
Published in2017 International Conference on Computer Network, Electronic and Automation (ICCNEA) pp. 480 - 485
Main Authors Jingzhu Li, Changxing Geng, Peng Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Calibration
Correlation
Cucumber downy mildew
Disease assessment
Diseases
Feature extraction
human eyes assessment
Image color analysis
Image processing
linear correlation
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Summary:Cucumber downy mildew is a kind of disease which spreads very fast and isdangerous, in order to prevent the disease, peoplealways spray plenty of pesticides indiscriminately. Accurate assessment of the level of cucumber downy mildew is very important to the disease prevention and control. In a cucumber growing season, this paper collected the typical cucumber downy mildew leaf samples, and developed the downy mildew spot extraction algorithm by using leaf image scanning method, calculated the index of the disease. The average identification accuracy of downy mildew image reaches 98.3%, and average image processing takes 10.9 ms/picture. By compared with human eyes assessment and basic value, the result shows that the human eyes assessment method have strong subjectivity, dramatic changes and bigger error, while the image analysis method get the correlation coefficient for disease index and basic value of 0.9417, has obvious linear correlation.
DOI:10.1109/ICCNEA.2017.65