Video-equipped fire detection method based on multi-characteristic fusion

A multi-feature fusion and flame detection technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of low algorithm reliability and achieve high accuracy, good application prospects, and low false detection rate.

Active Publication Date: 2017-06-13
FUJIAN CHUANZHENG COMM COLLEGE
View PDF7 Cites 36 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Video flame detection technology is easily affected by complex scenes, interference objects similar to flame color and lighting conditions, which makes the reliability of the algorithm not high, and is still in the initial stage of research

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
  • Video-equipped fire detection method based on multi-characteristic fusion
  • Video-equipped fire detection method based on multi-characteristic fusion
  • Video-equipped fire detection method based on multi-characteristic fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0076] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0077] Please refer to figure 1 , the present invention provides a kind of video flame detection method based on multi-feature fusion, it is characterized in that, comprises the following steps:

[0078] Step S1: read the first frame of image;

[0079] Step S2: Initialize the selective background update model and set the pixel accumulator;

[0080] Step S3: read the next frame of image;

[0081] Step S4: Carry out moving object detection based on the selective background update model, and determine whether there is a moving object, and if so, perform color detection on the moving object, otherwise return to step S3;

[0082] When there is a fire, the flame presents a dynamic characteristic of changing and developing from scratch. In this system, firstly, the moving foreground object is segmented through the moving object detection, and the static in...

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 a video-equipped fire detection method based on multi-characteristic fusion. Firstly, an improved selective background update model is adopted to acquire moving foreground objects in video images; then, through fire color detection and identification, suspicious fire objects are extracted, and stroboscopic characteristic, sharp-corner characteristic, circularity characteristic, area increasing characteristic and overall movement characteristic of fire are analyzed; finally, a fire multi-dynamic-characteristic fusion detection and identification method based on an analytic hierarchy process (AHP) is proposed. The method can be used for accurately and effectively detecting and identifying fire information in videos.

Description

technical field [0001] The invention relates to the field of flame detection, in particular to a video flame detection method based on multi-feature fusion. Background technique [0002] Visual flame detection is one of the topics of great theoretical significance and practical value in machine vision, and it is a research hotspot in the field of flame detection at present. The flame monitoring method based on video images can effectively overcome the disadvantages of traditional non-contact detectors such as small detection distance, large environmental impact and single fire criterion, which can help improve the accuracy and reliability of fire detection. [0003] At present, many scholars have proposed many detection methods on flame image detection and recognition. The following are the existing references on flame image detection: [0004] [1] Bugaric M, Jakovcevic T, Stipanicev D.Adaptive estimation of visual smoke detection parameters based on spatial data and fire r...

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): G06K9/00G06K9/62
CPCG06V20/46G06F18/2411G06F18/253
Inventor 曾思通刘克陈天炎王水发张伟张志川
Owner FUJIAN CHUANZHENG COMM COLLEGE
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products