Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Rainfall inspection method based on image recognition algorithm

A technology for image recognition and precipitation inspection, applied in 2D image generation, image enhancement, image analysis, etc., can solve problems such as inability to objectively analyze precipitation, achieve good model correction, and improve accuracy

Pending Publication Date: 2021-09-10
南京气象科技创新研究院
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a precipitation inspection method based on an image recognition algorithm, which solves the problem that the existing precipitation forecast cannot objectively analyze the precipitation and cannot meet people's requirements

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Rainfall inspection method based on image recognition algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0027] refer to figure 1 , a precipitation inspection method based on an image recognition algorithm, comprising the following steps:

[0028] S1: Data reading, first collect meteorological raw data and pictures, then identify and read them, and then perform image enhancement, image denoising, image filtering, image segmentation, image integration and image binarization processing in sequence to obtain preprocessing image;

[0029] S2: Data analysis, analyze the read data, and then set the precipitation threshold, define the continuous precipitation area through the precipitation threshold, and identify and separate the continuous precipitation area in a specific area;

[0030] S3: Data processing, shifting the model forecast at various angles to minimize the variance between the model precipitation forecast and the actual situation, calculate and analyze the precipitation fall area, precipitation intensity, and shape errors between the actual situation and the model, and sol...

Embodiment 2

[0035] refer to figure 1 , a precipitation inspection method based on an image recognition algorithm, comprising the following steps:

[0036] S1: Data reading, first collect meteorological raw data and pictures, then identify and read them, and then perform image enhancement, image denoising, image filtering, image segmentation, image integration and image binarization processing in sequence to obtain preprocessing image;

[0037] S2: Data analysis, analyze the read data, and then set the precipitation threshold, define the continuous precipitation area through the precipitation threshold, and identify and separate the continuous precipitation area in a specific area;

[0038] S3: Data processing, shifting the model forecast at various angles to minimize the variance between the model precipitation forecast and the actual situation, calculate and analyze the precipitation fall area, precipitation intensity, and shape errors between the actual situation and the model, and sol...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of rainfall inspection, and discloses a rainfall inspection method based on an image recognition algorithm, which comprises the following steps: S1, data reading: firstly, collecting meteorological original data and pictures, then recognizing and reading the meteorological original data and pictures, and sequentially performing image enhancement, image denoising, image filtering, image segmentation, image integration and image binarization processing to obtain a preprocessed image; and S2, data analysis: analyzing the read data, and then setting a precipitation threshold value. According to the invention, the mode forecasting is translated at all angles, so that the variance of the mode rainfall forecasting and the actual condition is minimum, the rainfall falling area, rainfall intensity and form error of the actual condition and the mode are calculated and analyzed, and the problem that the rainfall forecasting capability judgment of a numerical mode is not objective enough is solved; the rainfall error of the numerical mode under different influence systems can be more conveniently understood by a predictor, so that mode correction can be better carried out, and accurate rainfall forecast can be made.

Description

technical field [0001] The invention relates to the technical field of precipitation inspection, in particular to a precipitation inspection method based on an image recognition algorithm. Background technique [0002] For a long time, the serious consequences of natural disasters have made people extremely vigilant, and in natural disasters, except for a few types of disasters such as drought, most of them are more or less related to precipitation disasters, either directly or indirectly. Weather The process is the change process of weather phenomena in a certain area over time. Various weather systems have certain spatial and temporal scales, and systems of various scales interweave and interact with each other. The combination of many weather systems constitutes a large-scale weather situation and the hemispheric or even global atmospheric circulation. The weather system is always in the process of continuous birth, development and extinction, and has its corresponding ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/11G06T11/20G06F16/248G06F16/29
CPCG06T7/11G06T11/206G06F16/248G06F16/29G06T5/70
Inventor 曾明剑李昕张冰王文兰周嘉陵梅海霞张备唐飞杜良永
Owner 南京气象科技创新研究院
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products