Computer vision-based rice disease, pest and weed diagnostic method

Abstract

The invention relates to a computer vision-based rice disease, pest and weed diagnostic method. The method comprises the following steps: collecting different varieties of rice leaf disease samples at different morbidity periods in different growth environments, and letting a plant disease expert identify the diseases infecting all the samples; then acquiring images of disease symptoms of the samples; realizing the automatic segmentation of disease spots by utilizing an image processing technology; extracting all characteristic indexes of the disease spots, and establishing a characteristic database corresponding to the diseases; on the basis, selecting proper disease spot characteristic parameters and an effective pattern recognition algorithm so as to establish a machine vision-based rice disease, pest and weed real-time diagnostic model.

Description

technical field

[0001] The invention relates to a real-time diagnosis method and system based on machine vision, in particular to a method for diagnosing rice diseases, insect pests and weeds based on computer vision. Background technique

[0002] With the rapid development of information science and technology, computer vision technology has been involved in the identification and diagnosis of plant diseases and insect pests, weed identification, seed quality inspection, product quality inspection and classification, etc., and has achieved a series of results. Pests and diseases occur throughout the growth period of crops, and the annual loss is quite staggering. The application of chemical pesticides can greatly reduce agricultural losses, but the "three causes" problems, "three Rs" problems, pesticide residues, and environmental problems caused by non-standard use of chemical pesticides Negative effects such as pollution are gradually revealed. Research on automatic dete...

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