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Identification of pumpkin powdery mildew based on image processing PCA and machine learning

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Abstract

A method based on image processing, principal component analysis (PCA) and machine learning was proposed to identify pumpkin powdery mildew and improve the identification accuracy of pumpkin powdery mildew. The leaf-disease image was processed by the color feature compositing and detection method,in order to segment the lesion more accurately. Then 20 feature values are extracted, including the texture features, color features and morphological features of the segmented lesions, and the 20-dimensional original feature parameters were simplified to 3-dimensional feature parameters via the PCA method. Finally, three different SVM kernel functions are used to construct the classification model to compare the original feature parameters and principal component feature parameters separately. Experiment results show that the effect of illumination angle and intensity can be effectively eliminated after the super red feature calculation, and that the SVM model based on PCA and polynomial kernel function has a better recognition effect on pumpkin powdery mildew. The recognition rate is 97.3%, which is 3.15% higher than that of the traditional original characteristic parameters. Based on this finding, it can be concluded that this machine learning model can achieve accurate lesions identification.

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Funding

The research is funded by Jiangsu Provincial Natural and Science Founding (BK20170727), National Natural Science Foundation of China (61701242) and Special Plan for Innovation and Entrepreneurship Training for College Students of Nanjing Agricultural University(S20190036).

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Authors and Affiliations

  1. College of Engineering, Nanjing Agricultural University, Nanjing, 210031, People’s Republic of China

    Hong Lin, Hang Sheng, Guoxiang Sun, Yuhua Li, Maohua Xiao & Xiaochan Wang

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  1. Hong Lin
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  2. Hang Sheng
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  3. Guoxiang Sun
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  4. Yuhua Li
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  5. Maohua Xiao
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Correspondence to Xiaochan Wang.

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Lin, H., Sheng, H., Sun, G. et al. Identification of pumpkin powdery mildew based on image processing PCA and machine learning. Multimed Tools Appl 80, 21085–21099 (2021). https://doi.org/10.1007/s11042-020-10419-1

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