Flame detection method based on image target detection

A flame detection and target detection technology, which is applied in the fields of image processing, fire detection and video surveillance, can solve the problems of poor adaptability to environmental changes and the lack of image flame detection methods

Active Publication Date: 2018-09-14
TSINGHUA UNIV
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Problems solved by technology

This process still needs to utilize the color characteristics and dynamic characteristics of the flame, which leads to poor adaptability of its det...

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  • Flame detection method based on image target detection
  • Flame detection method based on image target detection
  • Flame detection method based on image target detection

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specific Embodiment

[0100] A specific embodiment of the present invention is as follows:

[0101] A kind of flame detection method based on image target detection that the present embodiment proposes, comprises the following steps:

[0102] 1) Collect N (N=5075) color pictures with flame pictures, and establish a flame picture data set F image . The pictures collected are all collected from the Internet, and all of the pictures contain obvious pictures of flames.

[0103] 2) For the flame picture data set F of step 1) image The position coordinates of the flame area of ​​each picture in the image are manually marked with a rectangular box, such as image 3 As shown in (a) and (b), the flame area is framed with a rectangular frame, and the real label frame of the flame area position and the 4 coordinate values ​​of the real label frame in each picture are obtained: l=1,2,...,N, where is the position coordinate of the vertex in the upper left corner of the real label frame of the lth picture...

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Abstract

The invention provides a flame detection method based on image target detection, which belongs to the field of image processing, fire detection and video monitoring. The method comprises steps: firstly, a flame detection data set containing flame images and annotation information of each image is built, and the flame detection data set is divided to a training set and a test set; a deep convolution neural network model is built, the training set is used to carry out iterative updating on the model, the test set is used to calculate a loss function for the updated model, and if the loss function for the current model does not drop any more, the model completes training; and a real-time video is photographed, the model which completes training is used to detect each frame of image, if flameexists, the coordinate position of the flame in the image is outputted by the model, and a rectangular frame is used for marking. The phenomenon that features are manually designed for generating a candidate area for suspected flame is not needed, the deep convolution neural network model can be directly used for carrying out flame detection on the whole image, the position information of the flame is obtained, early warning of a fire is thus carried out, and hazards brought by fire can be reduced maximally.

Description

technical field [0001] The invention relates to the fields of image processing, fire detection and video surveillance, in particular to a flame detection method based on image target detection. Background technique [0002] Fire is a kind of frequent disaster that seriously endangers the safety of people's lives and property. Early warning of fire can prevent the spread of fire and minimize the harm caused by fire. For flame detection tasks, especially those in outdoor and large indoor spaces, ordinary physical sensors cannot be effectively completed. Therefore, flame detection methods based on image processing technology are currently an important research direction in the field of safety engineering. [0003] The development of flame detection method based on image processing technology mainly has two stages. The first stage is to judge whether there is a flame in the image according to the visual characteristics such as the color, shape, and texture of the flame, combine...

Claims

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Application Information

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IPC IPC(8): G06K9/20G06K9/62G06T7/00G06T7/90G06N3/08
CPCG06N3/084G06T7/0002G06T7/90G06V10/22G06F18/23
Inventor 赵劲松吴昊
Owner TSINGHUA UNIV
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