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Flame identification method based on video image brightness

A flame recognition and video image technology, which is applied in the field of flame recognition based on video image brightness, can solve problems such as low accuracy, low efficiency, and long delay, and achieve the effects of reducing losses, improving accuracy, and avoiding wrong segmentation

Pending Publication Date: 2021-08-06
SOUTHEAST UNIV
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Problems solved by technology

[0003] In view of this, the purpose of the present invention is to provide a flame recognition method based on video image brightness to solve the problems of low accuracy, low efficiency, and large time delay caused by using sensors for detection in traditional fire detection.

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  • Flame identification method based on video image brightness
  • Flame identification method based on video image brightness
  • Flame identification method based on video image brightness

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Embodiment 1

[0049] see Figure 1-Figure 2 , the present embodiment provides a flame recognition method based on video image brightness, comprising the steps of:

[0050] Step S1, first read the video stream information, and capture a frame of image therein, as the basic information for the implementation of this method. The original information is generally the RGB information of the image, and each channel value of the corresponding pixel point (x, y) is R(x, y), G(x, y), B(x, y) based on this, Through the conversion relationship between the RGB color space and the YCbCr color space, the YCbCr information of the image is obtained, and each channel value of the corresponding pixel point (x, y) is Y(x, y), Cb(x, y), Cr(x , y), for use in subsequent algorithms.

[0051] Specifically, R(x, y), G(x, y), and B(x, y) respectively represent the values ​​of the red, green, and blue components of the pixel at the (x, y) spatial position; Y (x, y), Cb(x, y), and Cr(x, y) represent the difference...

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Abstract

The invention discloses a flame identification method based on video image brightness, and researches a flame identification algorithm taking brightness as a reference in consideration of different brightness when flame occurs and incapability of segmenting an effective flame part according to a single flame segmentation technology adopted by most algorithms, and flame identification can be realized in various environments more effectively. The method comprises the following steps: firstly, reading video image information; dividing the image into a high-brightness image and a low-brightness image according to a brightness criterion, and respectively adopting a high-brightness flame segmentation algorithm and a low-brightness flame segmentation algorithm to obtain a suspected flame region; carrying out morphological processingon the area to obtain a low-noise image with small holes filled; extracting the characteristics of circularity, color moment, texture and the like of the segmented parts, and combining the characteristics into characteristic vectors; and finally, carrying out flame classification by using a support vector machine. The accuracy and reliability of flame recognition are improved, the use effect is good, and the method is suitable for complex and changeable environments.

Description

technical field [0001] The invention relates to the field of fire flame identification, in particular to a flame identification method based on video image brightness. Background technique [0002] In the traditional fire detection, it mainly relies on sensors such as temperature, smoke and light, and judges whether there is a fire when the data of the sensor reaches a certain size. However, there are big problems in this method, mainly in the fire detection In terms of scope, accuracy and timeliness: When the environment space where the sensor is placed is large, a single sensor cannot meet the requirements very well, and a large number of nodes need to be deployed for detection, resulting in waste of resources; the accuracy of the sensor itself and the environment The influence of other factors such as light, smog and other factors will greatly affect the detection results, resulting in low accuracy, high false alarm rate, and unnecessary waste of human resources; the occu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06T7/11
CPCG06T7/11G06T2207/10024G06V20/41G06V20/46G06V10/56G06F18/214G06F18/2411
Inventor 胡静宋铁成杜朝明夏玮玮燕锋沈连丰
Owner SOUTHEAST UNIV
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