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

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 ...

AI Technical Summary

Problems solved by technology

However, for fire detection engineering, it is difficult to obtain labeled training samples required by large-scale target detection networks, and because these algorithms have a large amount of computation, it is difficult to ensure real-time detection in a monitoring environment

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