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Wheat lodging area extraction system and method

An extraction system, wheat technology, applied in the details of image stitching, image data processing, instruments, etc., can solve the problems of low, only applicable, time-consuming and labor-intensive, affecting mapping, etc.

Pending Publication Date: 2022-03-11
CHINA AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The manual survey method requires staff to observe, measure and count crop lodging information on the spot. This method is time-consuming, laborious, and inefficient, and is only suitable for small-scale crop lodging investigations; It shows different texture differences and also has different spectral reflectance. The remote sensing image method can distinguish ground objects by analyzing these differences.
This method can obtain a large area of ​​wheat remote sensing images at one time, and the efficiency is much higher than that of manual methods. However, there are still some problems in the survey method based on remote sensing: the image acquisition is greatly affected by the weather, and cloudy, rainy and snowy weather will seriously affect the mapping; The reentry cycle to a fixed location is relatively long, and it cannot be guaranteed that the image of the research area can be fully acquired at one time

Method used

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  • Wheat lodging area extraction system and method
  • Wheat lodging area extraction system and method

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0073] 1. Experimental process

[0074] 1.1 Aerial images

[0075] A UAV equipped with a multispectral sensor was used to obtain images of winter wheat in the experimental area.

[0076] 1.2 Image Analysis

[0077] 1.2.1 Preprocessing

[0078] The collected field image data were preprocessed, including image stitching, geometric correction, and radiometric calibration, to obtain multispectral images of the wheat canopy.

[0079] 1.2.2 Calculating texture features

[0080] For the obtained winter wheat canopy multispectral image, the following methods are used to extract texture features:

[0081] Use the filter tool based on second-order probability statistics to calculate the texture information of normal winter wheat and lodging winter wheat. The processing window of the filter is set to 7*7, and the reference window is used as a reference. The spatial correlation matrix transformation values ​​X and Y are both 1, and the grayscale The quality level is 64; after texture...

Embodiment 2

[0091] The influence of embodiment 2 different flight heights

[0092] The lodging area of ​​winter wheat was extracted according to the method in Example 1, wherein the flying heights were 30 meters, 40 meters and 50 meters respectively. The obtained classification error results are shown in the table below, and the results show that the effect is the best when the flying height is 50 meters.

[0093] overall classification accuracy Kappa coefficient RGB1_30m 96.9182％ 0.9286 RGB1_40m 98.4609％ 0.9650 RGB1_50m 99.4602％ 0.9875

Embodiment 3

[0094] The influence of embodiment 3 different flight times

[0095] The lodging area of ​​winter wheat is extracted according to the method of Example 1, wherein the flight time is respectively 9:00~10:00 (RGB1) in the morning, 13:00~14:00 (RGB2) in the noon, and 17:00~18:00 in the afternoon ( RGB3). See the table below for the obtained classification error results. The results show that the flight time is between 9:00 am and 10:00 am, and the effect is the best.

[0096] overall classification accuracy Kappa coefficient RGB1_50m 99.4602％ 0.9875 RGB2_50m 95.5221％ 0.8990 RGB3_50m 99.2305％ 0.9822

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Abstract

The invention provides a wheat lodging area extraction system and method, and the system comprises an obtaining unit which is used for obtaining field image data of a test area through a multi-spectral sensor carried by an unmanned plane; the preprocessing unit is connected with the acquisition unit and is used for processing the acquired field image data of the test area to obtain a wheat canopy multispectral image; the calculation unit is connected with the preprocessing unit and is used for calculating texture features of a target crop in the wheat canopy multispectral image; and the selection unit is connected with the calculation unit, and is used for respectively merging the calculated texture features with the multispectral images, carrying out classification analysis on the images by using a mahalanobis distance classification method, and extracting the lodging area of the wheat. The extraction system and method can accurately extract the lodging area of the wheat, reduce the labor cost and are suitable for large-scale popularization and application.

Description

technical field [0001] The invention relates to the field of ground observation and crop phenotype extraction based on drone images, in particular to a system and method for extracting wheat lodging area. Background technique [0002] Wheat is the food crop with the largest sown area and the largest yield in the world, and its growth and yield affect world food security. Lodging often occurs in the process of wheat growth and is a common agricultural disaster. There are many reasons for lodging, and severe weather and the lodging resistance of wheat varieties have the greatest impact. After lodging, wheat is prone to disease, resulting in reduced quality. Lodging of wheat also increases the difficulty of mechanical harvesting. Therefore, after lodging occurs, failure to obtain lodging information in time will affect the production evaluation of relevant departments. [0003] Manual survey method and remote sensing image method are two commonly used methods to obtain wheat ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/10G06V10/143G06V10/774G06V10/764G06K9/62G06T3/40G06T5/00G06T7/40G06T7/62G06T7/90
CPCG06T7/40G06T7/90G06T3/4038G06T7/62G06T2207/30188G06T2200/32G06F18/214G06F18/241G06T5/80
Inventor 刘哲张心璐昝糈莉李绍明张晓东邢子瑶
Owner CHINA AGRI UNIV