Plant disease and insect pest identification method based on deep learning
A technology of deep learning and identification methods, applied in the field of plant pest identification based on deep learning, can solve problems such as low image recognition rate, low prediction accuracy, complex model structure, etc., and achieve reliable calculation, simplified model structure, and simple structure Effect
Pending Publication Date: 2020-04-28
JILIN AGRICULTURAL UNIV
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[0005] In order to solve the problems of low image recognition rate, complex model structure, and low prediction accuracy existing in the existing methods for classification and recognition of crop pests and diseases based on deep learning algorithms, the present invention provides a method for identifying plant diseases and pests based on deep learning
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[0055] The method for identifying plant diseases and insect pests based on deep learning of the present invention mainly comprises the following steps:
[0056] Step 1. Image Acquisition
[0057] The leaf images of plant diseases and insect pests and the images of normal plant leaves are obtained through camera shooting, web page download or mobile app download.
[0058] Step 2. Image preprocessing
[0059] 1. Unify the image size and format; the image size is 640x480, RGB format, and the format is jpg, png, gif or tif.
[0060] 2. Perform Fourier transform on the leaf images of plant diseases and insect pests and normal plant leaves to obtain the corresponding Fourier transform spectrum S 1 (x,y) and S 2 (x,y).
[0061] 3. Use the Fourier transform spectrum to calculate the objective function, the formula is as follows:
[0062]
[0063] In the formula, I 1 (x, y) is the optical transfer function of the leaf image of plant diseases and insect pests, I 1 * (x,y) is ...
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The invention discloses a plant disease and insect pest identification method based on deep learning, relates to the field of plant disease and insect pest prevention and control, and solves the problems of low image identification rate, complex model structure and low prediction accuracy of an existing crop disease and insect pest classification and identification method. The method comprises thesteps of collecting a plant disease and insect pest leaf image and a normal plant leaf image; preprocessing the image to obtain a super-resolution plant disease and insect pest leaf target image; fusing, analyzing and calculating the super-resolution plant disease and insect pest leaf target image through a deep learning algorithm to generate a plant disease and insect pest image feature expression; analyzing and calculating the plant disease and insect pest image feature expression through a deep learning network to generate a plant disease and insect pest identification model based on the deep learning network; and training a plant disease and insect pest leaf image needing to be identified by utilizing the plant disease and insect pest identification model based on the deep learning network. The method is high in image recognition rate, simple in model structure and high in prediction accuracy.
Description
technical field [0001] The invention relates to the technical field of plant disease and insect pest control, in particular to a method for identifying plant disease and insect pests based on deep learning. Background technique [0002] During the growth of crops, they will encounter various kinds of pests and diseases, which will have a great impact on the yield and quality of crops. Pests and diseases are collectively called diseases and insect pests. Infectious diseases are divided into: fungal diseases according to different pathogenic organisms, which can cause plant lodging, dead seedlings, spots, black fruit, wilting and other symptoms, with obvious mildew on the diseased part Layers, black spots, powder and other phenomena. Bacterial disease, manifested as wilting, rot, perforation, etc., in the late stage of the disease in wet weather, bacterial mucus overflows on the diseased part, which is the characteristic of bacterial diseases. Viral diseases, manifested as m...
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IPC IPC(8): G06T3/40G06T7/11G06T7/187G06K9/62G06N3/04G06N3/08
CPCG06T3/4053G06T3/4023G06T7/11G06T7/187G06N3/08G06N3/045G06F18/24323
Inventor 徐兴梅刘远周晶陈谦王硕王宁于孝铂
Owner JILIN AGRICULTURAL UNIV