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Comprehensive flame detection method based on ultraviolet and binocular vision

A binocular vision and flame detection technology, applied in the field of image analysis, can solve the problems of difficulty in simultaneous satisfaction, reduction of detection rate and false detection rate, etc., to reduce the probability of false detection and missed detection, fast response, strong robustness sexual effect

Pending Publication Date: 2020-05-19
成都视道信息技术有限公司
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AI Technical Summary

Problems solved by technology

Most of the existing algorithms for fire detection by image processing technology use some fixed thresholds, which makes it difficult to improve the detection rate and reduce the false detection rate at the same time.

Method used

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  • Comprehensive flame detection method based on ultraviolet and binocular vision
  • Comprehensive flame detection method based on ultraviolet and binocular vision
  • Comprehensive flame detection method based on ultraviolet and binocular vision

Examples

Experimental program
Comparison scheme
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Embodiment

[0108] 1. Environmental monitoring

[0109] Use the ultraviolet fire detector to detect the ultraviolet spectrum in the 180-240nm band in the current environment. If the ultraviolet spectrum in this band is detected, the camera will be triggered to take a snapshot.

[0110] 2. Motion detection

[0111] To analyze the captured pictures, first perform motion detection on the captured pictures. Background subtraction is currently one of the simplest and most efficient methods for motion recognition. In order to obtain an accurate foreground image, an important step in background subtraction is how to establish an accurate background image. The method of background modeling currently mainly uses the MOG2 algorithm. The OpenCV3.0 version adds a KNN background modeling algorithm. In the case of a small number of moving objects, the KNN algorithm is slightly more accurate in establishing the resulting background image. It is better than the MOG2 algorithm, but in terms of processin...

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Abstract

The invention provides a comprehensive flame detection method based on ultraviolet and video. The method comprises the following steps: S1, carrying out real-time detection on a monitoring environmentthrough an ultraviolet and binocular vision composite flame detector, firstly, detecting a flame ultraviolet spectrum through an ultraviolet sensor, and triggering a video camera to carry out snapshot under an abnormal condition, so as to obtain current environment image data; S2, performing image analysis on the obtained video image data, and using motion detection to segment a suspected flame region image based on region growth in combination with an HSI color model; judging the suspected flame region through flame characteristic detection; according to camera parameters, carrying out binocular vision reconstruction to obtain the actual flame area and distance; and S3, judging the flame grade of the flame at the current moment and in the whole combustion process according to the actualarea of the flame.

Description

technical field [0001] The invention relates to the field of image analysis, in particular to a comprehensive flame detection method based on ultraviolet and binocular vision. Background technique [0002] Currently, there are two common methods for fire detection. According to the relationship between the detection element and the detection object, the fire detection principle can be divided into two basic types: contact and non-contact. Contact detection mainly includes temperature-sensing and smoke-sensing fire detectors, and non-contact detection mainly includes image detectors. [0003] 1. The temperature detector responds to a fire detector with abnormal high temperature or abnormal temperature rise rate. Temperature-sensitive fire detectors are more reliable than smoke detectors and have lower environmental requirements. However, the response to the initial fire is slow, and it is not suitable for use in places where black smoke, dust, steam and oil mist may be gene...

Claims

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Application Information

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IPC IPC(8): G06T7/11G06T7/20G06T7/254G06T7/80G06T7/90G06K9/62G06K9/20
CPCG06T7/20G06T7/11G06T7/90G06T7/80G06T7/254G06V10/143G06F18/23
Inventor 刘伟方黎勇王思维
Owner 成都视道信息技术有限公司
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