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

Wildfire detection method based on image intelligent analysis

A technology of intelligent analysis and detection methods, applied in image analysis, image data processing, instruments, etc., can solve the problems of increasing the difficulty of fire detection, distinguishing background and wild fire, affecting feature extraction, etc., achieving ideal segmentation effect and satisfying real-time performance Requirements, low-complexity effects

Active Publication Date: 2017-10-24
STATE GRID CORP OF CHINA +3
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although these threshold-based methods are fast and simple, they are very sensitive to the selection of the threshold. Due to the complexity of the forest environment, it is often difficult to select a suitable threshold to distinguish the background from the wildfire.
If the mountain fire area cannot be extracted more accurately, it will affect the subsequent feature extraction, thus increasing the difficulty of fire detection

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
  • Wildfire detection method based on image intelligent analysis
  • Wildfire detection method based on image intelligent analysis
  • Wildfire detection method based on image intelligent analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0035] Such as figure 1 with figure 2 As shown, a wildfire detection method based on intelligent image analysis includes the following steps:

[0036] (1) The training phase, which is divided into the following three steps:

[0037]Step 1. Build a database: Collect pictures about wildfires from the Internet, mark the location of wildfires by manual labeling, and mark the category of each picture;

[0038] Step 2, SLIC obtains superpixels: Given a training image, use SLIC method to extract superpixels of the image, set the size of the superpixel block to be larger than 20 pixels, and set the normalization parameter of SLIC to 0.01, Make the superpixel block it generates coincides with the ou...

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 discloses a mountain fire detection method based on intelligent image analysis, which includes a training stage and a test stage. The superpixels of the image are obtained by using the SLIC method. The method can quickly cluster the pixels of the image, and can perform well After fitting the edge of the target accurately, after obtaining the superpixel block, its color and texture features are proposed, and the image is classified according to these features. The fire detection method based on texture and color proposed by the present invention can quickly and effectively detect the location of wildfires, and can achieve a more accurate classification result. The superpixels generated by SLIC used in this method can fit the edge of the target well, and the segmentation effect is ideal. The features used to describe the superpixel region are simple and effective, with low complexity, which can meet the real-time requirements of wildfire detection.

Description

technical field [0001] The invention relates to a mountain fire detection method, in particular to a mountain fire detection method based on image intelligent analysis. Background technique [0002] Forest fires refer to fires that occur in the mountains and cause great damage to the forest ecosystem and the safety of human life and property and are difficult to control. They are characterized by strong suddenness, wide coverage, fast spread, and high danger. With global warming, the occurrence of forest fires is becoming more and more frequent. Our country attaches great importance to the prevention and protection of wildfires, aiming to effectively extinguish wildfires in the early stages of their occurrence and prevent their damage to the environment and human life and property. Early fire detection mainly relied on staff patrolling. This method not only consumes a lot of manpower and material resources, but human patrols will inevitably lead to some negligence, and in s...

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 Patents(China)
IPC IPC(8): G06K9/62G06T7/90
CPCG06V10/56G06F18/23G06F18/2411G06F18/24137
Inventor 姚楠罗旺郭雅娟洪功义张天兵
Owner STATE GRID CORP OF CHINA
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com