Fire image detection method based on mixed color model and neural network

A color model and neural network technology, applied in neural learning methods, biological neural network models, fire alarms that rely on radiation effects, etc., can solve the problem of difficulty in obtaining labeled training samples for large-scale target detection networks, large amount of computation, and Difficult to ensure real-time detection and other issues, to achieve the effect of high detection accuracy, good connectivity, and less mask holes

Active Publication Date: 2019-08-16
HANGZHOU DIANZI UNIV
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Problems solved by technology

However, for fire detection engineering, it is difficult to obtain labeled training samples required by large-scale target detection network

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  • Fire image detection method based on mixed color model and neural network
  • Fire image detection method based on mixed color model and neural network
  • Fire image detection method based on mixed color model and neural network

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Embodiment Construction

[0058] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0059] refer to figure 1 Shown flow chart, a kind of fire image detection method based on mixed color model and neural network that the present invention proposes, specifically comprises the following steps:

[0060] Step (1). Utilize inter-frame difference method to obtain the moving foreground target of monitoring video frame:

[0061] (1-1). By comparing the difference between the two frames of images in the video before and after, to identify whether there is a moving object, the expression of the foreground mask of the moving foreground is:

[0062]

[0063] Among them, fmask (x, y) is the differential image of the front and rear frame images, that is, the moving foreground mask, 255 means that the moving target is set to white on the grayscale image, 0 means that the non-moving area is set to black, I t and I t-1 Represent...

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Abstract

The invention discloses a fire image detection method based on a mixed color model and a neural network. The method comprises the following steps: firstly, performing an inter-frame difference methodon a monitoring video image to obtain a moving foreground region; extracting an area conforming to flame color characteristics through the mixed color model, and performing secondary color area expansion to obtain candidate areas filtered by the color model; taking a union set of the motion foreground area and the color candidate area to obtain a suspected flame area; and finally, constructing a dense connection convolutional neural network, and comprehensively judging whether a suspected flame region has a fire behavior or not through the trained network model and the secondary mixed color model. According to the method, the flame candidate area with high precision is obtained through motion detection and the mixed color model, the detection speed is high, the deep neural network guarantees the flame detection accuracy and the generalization capability, the method can be widely deployed in an actual intelligent security system, fire hazards are early warned, and losses caused by the fire hazards are reduced.

Description

technical field [0001] The invention belongs to the technical field of image processing and target detection, and in particular relates to a fire image detection method based on a mixed color model and a neural network. Background technique [0002] In modern society, the frequent occurrence of fire accidents threatens the safety of people's lives and properties. How to detect the occurrence of fires in real time and accurately has always been a key area of ​​concern for intelligent monitoring and security engineering, and it is also an important topic in the field of image recognition. With the continuous advancement of computer vision technology, it has become possible to detect the occurrence of fire in real time through surveillance video for a disaster accident with significant visual information. [0003] Existing fire detection technologies are divided into traditional fire recognition sensor detection and fire detection based on video images. Among them, traditional ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G08B17/12G06N3/08G06N3/04
CPCG08B17/125G06N3/08G06V20/40G06V10/255G06N3/045
Inventor 何志伟吴凡高明煜
Owner HANGZHOU DIANZI UNIV
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