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Rice lodging intelligent evaluation and loss assessment system based on deep learning and evaluation and loss assessment method thereof

A deep learning and rice technology, applied in image data processing, instrument, character and pattern recognition, etc., can solve problems such as inability to automatically match farmer information, low degree of automation, and inability to quantitatively determine losses, achieving a simple and clear structure and perfect system. , the effect of not easy to interfere

Pending Publication Date: 2020-02-04
黑龙江地理信息工程院
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  • Description
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  • Application Information

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Problems solved by technology

[0004] The present invention aims at the defects that the existing damage determination method cannot automatically match farmers’ information, cannot quantify damages, has poor practicality and low degree of automation, and provides a method that can match farmers’ information, quantitatively determine losses, has strong practicality, and is automated. High-level rice lodging intelligent evaluation and damage determination system based on deep learning and its evaluation and damage determination method

Method used

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  • Rice lodging intelligent evaluation and loss assessment system based on deep learning and evaluation and loss assessment method thereof
  • Rice lodging intelligent evaluation and loss assessment system based on deep learning and evaluation and loss assessment method thereof

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Embodiment 1

[0024] combine figure 1 and figure 2 Describe this embodiment. In this embodiment, a rice lodging intelligent evaluation and damage determination system based on deep learning involved in this embodiment includes an image fast spelling module, an image editing module, a disaster processing module and a confirmation sheet output module. , the image fast spelling function module realizes the fast splicing of the UAV image by calling the fast splicing software; Form a complete lodging image; the image editing function module includes an image data loading module, a polygon drawing module, an edge cleaning module, a cutting module and an image data storage module, which can realize the precise delineation of farmer plots; the image data loading module uses After loading the spliced ​​complete lodging image, the polygon drawing module is used to draw the right plot boundary on the spliced ​​lodging image according to the farmers' information, and the edge cleaning module is used ...

Embodiment 2

[0026] This embodiment is described in conjunction with Embodiment 1. In this embodiment, a kind of evaluation and damage determination method based on the described rice lodging intelligent evaluation and damage determination system based on deep learning involved in this embodiment includes the following steps:

[0027] Step 1. Obtain the drone image;

[0028] Step 2, the fast stitching software quickly stitches the overlapping UAV remote sensing sequence images, calls the UAV image quick stitching software, and obtains the UAV remote sensing sequence images with a certain degree of overlap after the UAV flight ends , according to the overlapping areas of the sequence images, fast stitching is performed to obtain an entire image including the entire plot of the farmer;

[0029] Step 3: The image data loading module loads the spliced ​​complete lodging image, the polygon drawing module is used to draw edges according to the complete lodging image, and the edge clearing module...

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Abstract

The invention discloses an intelligent rice lodging loss assessment system and method based on deep learning, belongs to the field of rice lodging loss assessment, and provides the intelligent rice lodging loss assessment system and method based on deep learning, which can be matched with farmer information and have the advantages of quantitative loss assessment, high practicability and high automation degree. According to the invention, quick splicing software is used for quickly splicing images of an unmanned aerial vehicle. An image data loading module is used for loading the spliced complete unmanned aerial vehicle image. A polygon drawing module is used for drawing right plots on the spliced images according to farmer information. A cutting module is used for cutting according to drawn polygons. A disaster situation recognition module is used for segmenting disaster areas according to a deep learning algorithm, and a disaster situation statistics module is used for counting disaster proportions; and a confirmation single output module is used for outputting a disaster assessment loss assessment report. The invention is mainly used for evaluation and loss assessment of rice lodging.

Description

technical field [0001] The invention belongs to the field of rice lodging damage determination, and in particular relates to a deep learning-based intelligent evaluation and damage determination system for rice lodging and an evaluation and damage determination method thereof. Background technique [0002] Crop lodging is the main cause of yield reduction and crop quality reduction in agricultural production. At present, there are few studies on crop lodging damage determination. In the patent literature with the publication number CN108169138A, a method for determining damage based on remote sensing of lodging disasters based on UAVs is described. It uses thermal infrared images, uses color features, texture features, and temperature features to construct a discrimination model for lodging areas to identify lodging. area and non-lodging area. Due to the use of thermal infrared images, this method requires that the flying height of the UAV should not be too high when collec...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/62G06T3/40G06K9/00
CPCG06T7/0002G06T7/62G06T3/4038G06T2207/30188G06T2207/20021G06T2207/20084G06V20/188
Inventor 巩翼龙
Owner 黑龙江地理信息工程院
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