Plant disease and pest detection method based on SVM (support vector machine) learning
A machine learning, pest and disease technology, applied in instruments, computer parts, character and pattern recognition, etc., can solve problems such as varying effects, achieve high practicability, easy operation, and avoid complex operation steps.
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[0048] Embodiment 1: the specific operation steps of the inventive method are as appended figure 1 As shown, firstly, in a large number of monitoring videos of agricultural scenes, a large number of normally growing plant leaves and plant leaves with diseases and insect pests are obtained, and a random sampling strategy is used to extract part of the pictures from the normal growing plant leaves and plant leaves with diseases and insect pests as Sample, extract features (including color features, HSV features, edge features and HOG features) for each leaf image, and combine these features into feature vectors; then use the SVM machine learning method to train the feature vectors of each leaf image, After training, a classifier is formed, and then a large number of plant leaf images are detected by this classifier to detect whether plant leaves are damaged by diseases and insect pests.
[0049] (1) Obtain images of a large number of plant leaves in agricultural scenes
[0050]...
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