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Fire detection method based on seed region growth rule in YCRCB color space

A technology of region growing and color space, which is applied in image data processing, instruments, character and pattern recognition, etc., can solve the problems of large calculation, low accuracy, and low efficiency of fire detection, etc., to reduce the calculation space and improve the speed effect on accuracy

Pending Publication Date: 2021-12-03
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

[0004] The invention provides a fire detection method based on the seed region growth rule in the YCRCB color space, which is used to solve the problems of low fire detection efficiency, low accuracy, large calculation degree and problems existing in the current fire detection algorithm in bright backgrounds. Problems with slow detection rates

Method used

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  • Fire detection method based on seed region growth rule in YCRCB color space
  • Fire detection method based on seed region growth rule in YCRCB color space
  • Fire detection method based on seed region growth rule in YCRCB color space

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Embodiment 1

[0080] Embodiment 1: as Figure 1-5 As shown, a fire detection method based on the seed region growth rule in the YCRCB color space, including image acquisition, frame image preprocessing, image pixel seed selection in the YCrCb channel by using the color characteristics of the fire, and the obtained seeds are based on the grayscale Based on the similarity criterion of value and chromaticity difference, the region is grown, and the dynamic characteristics of the flame image are discriminated on the grown image, and then the final discrimination result of the fire is obtained.

[0081] As a further solution of the present invention, the specific steps of the method are as follows:

[0082] Step1, collect suspected fire images through image acquisition equipment, and then perform image preprocessing; ensure that all noises are removed before the processing steps, and provide high-quality images for further operations on subsequent images;

[0083] Step2, convert the processed c...

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Abstract

The invention relates to a fire detection method based on a seed region growth rule in a YCRCB color space, and belongs to the technical field of fire detection. The method comprises the steps of collecting an image, performing frame image preprocessing, performing image seed selection in a YCrCb channel by using color characteristics of a fire, performing region growth on the obtained seed according to a gray value and chromaticity difference similarity criterion, and performing flame image dynamic characteristic discrimination on the grown image so as to obtain a final discrimination result of the fire. According to the method, the problems of low fire identification accuracy and high operation degree at present are solved, and the fire detection speed and accuracy can be effectively improved.

Description

technical field [0001] The invention relates to a fire detection method based on a seed region growth rule in a YCRCB color space, and belongs to the technical field of fire detection. Background technique [0002] Fire is a catastrophic event that can quickly cause significant injury and property damage. To reduce such hazards, early fire detection without false alarms is crucial. Therefore, various automatic fire detection technologies are being developed and widely used in real life. [0003] Most of the current fire area detection algorithms are based on RGB color images and some simple static and dynamic characteristics of fire for analysis, but fire images are obviously affected by background light. In similar cases, the detection effect is poor; in addition, the traditional method has a large amount of transportation, and needs to perform point-to-point operations on the entire image multiple times. Contents of the invention [0004] The invention provides a fire...

Claims

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Application Information

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IPC IPC(8): G06T7/62G06T7/136G06T7/11G06K9/46G06K9/34
CPCG06T7/62G06T7/11G06T7/136G06T2207/10024Y02A40/28
Inventor 杨雄飞管一弘王端生杨建菊余天兵李志强廖礼玲杨亚飞
Owner KUNMING UNIV OF SCI & TECH
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