A Crop Disease Identification Method Based on Probability Density Ratio
A crop disease and probability density technology, applied in character and pattern recognition, image data processing, instruments, etc., can solve the problem that it is not easy to detect crop diseases
Inactive Publication Date: 2017-07-07
XIJING UNIV
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However, the complexity of diseased leaves makes it difficult to detect crop diseases through leaf symptoms [H.Al-Hiary, S.Bani-Ahmad, M.Reyalat. Fast and Accurate Detection and Classification of Plant Diseases[J].International Journal of Computer Applications, 2011, 17(1): 31-38.]
At present, there are many types of crop diseases, resulting in various disease spot shapes on crop diseased leaves, which makes the research on disease identification methods based on crop diseased leaves challenging.
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[0063] The present invention will be described in detail below. * in the present invention represents a relationship of multiplication.
[0064] A crop disease recognition method based on probability density ratio, including four parts: disease spot segmentation of crop disease leaves, feature extraction of disease leaf images, dimensionality reduction of disease leaf feature vectors and disease identification.
[0065] First, the diseased spot segmentation of crop diseased leaves. First, collect and shoot images of crop diseased leaves {g 1 (x,y),g 2 (x,y),...,g n (x, y)}, use the function "imread" in Matlab software to convert all crop disease leaf images into digital images, and then convert the digital images into grayscale images. Any converted grayscale image is recorded as H(x,y); Let the number of pixels of H(x,y) be m, and the range of gray value i is [0,1,2,...,255]. If the number of pixels with gray value i is m i , then the proportion of the number of pixels ...
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The invention discloses a method for identifying crop diseases based on probability density ratio, which belongs to the technical field of image processing and pattern recognition. The steps of the method include: collecting and photographing images of crop diseased leaves, converting them into grayscale images and processing them to obtain color lesion images; processing the color lesion images to obtain feature vectors of each image; introducing probability density ratios The objective function is weighted, and the dimensionality reduction is performed on the feature vectors of the combined crop disease leaf images; the nearest neighbor classifier is used to classify the test samples. The invention has the advantages of fast feature extraction speed, high recognition rate, stable recognition effect, strong real-time performance, easy implementation and the like.
Description
technical field [0001] The invention relates to the technical field of identifying crop diseases by using diseased spots on crop diseased leaves, in particular to a method for identifying crop diseases based on probability density ratios. Background technique [0002] Crop diseases are the main reasons that seriously affect the quantity and quality of crop products in various countries. Early detection of crop diseases and accurate detection of disease types are the prerequisites for scientific prevention and control of crop diseases. Since crop leaves are the most abundant, occupy the most parts, and are the most convenient part to observe, and are also the parts that often appear first, leaf disease spots are one of the important bases for people to judge the occurrence of crop diseases and their degree of damage. The traditional crop disease detection method mainly relies on the agricultural grassroots guards and agricultural producers to diagnose the occurrence and degre...
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IPC IPC(8): G06K9/46G06T7/00
CPCG06T7/11G06T2207/10024G06F18/24147
Inventor 张善文师韵邓海生
Owner XIJING UNIV