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Recognition of plant leaf diseases based on computer vision

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Abstract

Agriculture is one of the most important sources of income for people in many countries. However, plant disease issues influence many farmers, as diseases in plants often naturally occur. If proper care is not taken, diseases can have hazardous effects on plants and influence the product quality, quantity or productivity. Therefore, the detection and prevention of plant diseases are serious concerns and should be considered to increase productivity. An effective identification technology can be beneficial for monitoring plant diseases. Generally, the leaves of plants show the first signs of plant disease, and most diseases can be detected from the symptoms that appear on the leaves. Therefore, this paper introduces a novel method for the detection of plant leaf diseases. The method is divided into two parts: image segmentation and image classification. First, a hue, saturation and intensity-based and LAB-based hybrid segmentation algorithm is proposed and used for the disease symptom segmentation of plant disease images. Then, the segmented images are input into a convolutional neural network for image classification. The validation accuracy obtained using this approach was approximately 15.51% higher than that for the conventional method. Additionally, the detection results showed that the average detection rate was 75.59% under complex background conditions, and most of the diseases were effectively detected. Thus, the approach of combined segmentation and classification is effective for plant disease identification, and our empirical research validates the advantages of the proposed method.

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Acknowledgements

The writers want to appreciate Pzcnet Ltd. (https://www.pzcnet.com/) and Mr. Wang Wen-Hua, director of research at the Fujian Institute of Subtropical Botany, for a valuable discussion and participation in the successful implementation of the project and beneficial comments. The author also likes to appreciate all the judges and editors whose useful suggestions helped improve the article.

Funding

This work is partly supported by grants from the National Natural Science Foundation of China (Project no. 61672439) and the Fundamental Research Funds for the Central Universities (#20720181004).

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Authors and Affiliations

  1. Informatics School of Xiamen University, Xiamen, 361005, Fujian, People’s Republic of China

    Y. A. Nanehkaran, Defu Zhang & Junde Chen

  2. School of Computer Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu, People’s Republic of China

    Yuan Tian

  3. Department of Computer Science, King Saud University, Riyadh, Kingdom of Saudi Arabia

    Najla Al-Nabhan

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  1. Y. A. Nanehkaran
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Correspondence to Defu Zhang.

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Nanehkaran, Y.A., Zhang, D., Chen, J. et al. Recognition of plant leaf diseases based on computer vision. J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-02505-x

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