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Wheat grain scab identification method based on imaging hyperspectral data

A wheat grain and recognition method technology, which is applied in image data processing, scene recognition, character and pattern recognition, etc., can solve the problem of no rapid identification of wheat grain head blight

Active Publication Date: 2019-04-19
ANHUI UNIVERSITY
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Problems solved by technology

[0007] The purpose of the present invention is to solve the defect that there is no method for quickly identifying wheat grain scab in the prior art, and to provide a method for identifying wheat grain scab based on imaging hyperspectral data to solve the above problems

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  • Wheat grain scab identification method based on imaging hyperspectral data
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  • Wheat grain scab identification method based on imaging hyperspectral data

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Embodiment Construction

[0042] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0043] Such as figure 1 As shown, a method for identifying wheat grain head blight based on imaging hyperspectral data according to the present invention comprises the following steps:

[0044] The first step is the collection of hyperspectral basic images. The hyperspectral basic image is collected by the hyperspectral imager, and the hyperspectral basic image includes images of healthy grains and diseased grains.

[0045] In the experimental stage, the wheat variety 987 was used as rotation selection. It was planted in the corn-wheat rotation plot of Xiaotangshan National Precision Agriculture Demonstration Base in September 2017. In 2018, on the first, third, and fifth days of wheat flowering, diseased wheat grains and Partial si...

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Abstract

The invention relates to a wheat grain scab identification method based on imaging hyperspectral data. Compared with the prior art, the defect that a method for rapidly identifying wheat grain scab does not exist is overcome. The method comprises the following steps: acquiring a hyperspectral basic image; Preprocessing the hyperspectral basic image; Constructing a wheat grain scab recognition model; Training a wheat grain scab identification model; Obtaining a to-be-identified hyperspectral image; Preprocessing the to-be-identified hyperspectral image; And identifying wheat grain scab. According to the invention, indoor hyperspectral imaging data is utilized; According to the method, wheat grains are segmented in a hyperspectral image through an image segmentation technology, then spectralinformation of the wheat grains is subjected to comparative analysis, an effective identification model of wheat scab disease infected wheat grains is established through data noise removal and characteristic wavelength screening, and a rapid and effective method for wheat grain scab detection is formed.

Description

technical field [0001] The invention relates to the technical field of hyperspectral data processing, in particular to a method for identifying wheat grain head blight based on imaging hyperspectral data. Background technique [0002] Fusarium scab is caused by Fusarium asiaticum and Fusarium graminearum and is a worldwide widespread crop disease. Wheat is the main food crop. The occurrence of scab will not only affect its yield Effective identification and detection of wheat scab and disease-infected wheat kernels have become the main content of current research in related fields. [0003] At present, the detection methods of wheat scab mainly include biochemical methods such as thin-layer chromatography, high-performance liquid chromatography, gas chromatography, and enzyme-linked immunoassay. However, most of the above methods require a high professional background. At the same time, they are time-consuming, require a large amount of manpower and material resources, and ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06T7/00G06T7/136
CPCG06T7/0002G06T7/136G06T2207/30188G06T2207/10036G06T2207/20081G06V20/194G06V20/13G06F18/2411G06F18/24323
Inventor 黄林生丁串龙杨贵军赵晋陵徐超梁栋黄文江翁士状张东彦
Owner ANHUI UNIVERSITY
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