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Forest fire identification method and device based on CN and three-channel capsule network

A forest fire and identification method technology, applied in the field of forest fire identification, can solve the problems of low detection efficiency and achieve the effect of improving accuracy

Active Publication Date: 2020-06-19
HENAN POLYTECHNIC UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the application limitations of the capsule network model itself, if the CapsNet network is directly used to detect the entire frame of images, it is necessary to divide the entire frame of images into different regions, and then apply the pre-trained flame detection CapsNet network for different regions. Detection, the detection efficiency is low, and it cannot meet the requirements for occasions with high real-time requirements

Method used

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  • Forest fire identification method and device based on CN and three-channel capsule network
  • Forest fire identification method and device based on CN and three-channel capsule network
  • Forest fire identification method and device based on CN and three-channel capsule network

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Embodiment 1

[0057] Embodiment 1 of the present invention discloses a forest fire identification method based on CN and three-channel capsule network, please refer to figure 1 As shown, it includes the following steps:

[0058] S110. Select forest fire images under different lighting conditions, and construct an initial sample set of forest fire flames; the initial sample set includes positive samples and negative samples.

[0059] The forest fire object has a strong particularity, and its small sample characteristics make it difficult to directly apply deep network training to the forest fire detection algorithm. It is still a challenging subject to apply forest fire detection to the actual detection system. In order to ensure the diversity and feasibility of samples, the selection of forest fire images includes most of the scenes where forest fires may occur, and the fire samples of the present invention include: daytime, night, cloudy, sunny, small fire spots. Negative samples include:...

Embodiment 2

[0086] Embodiment 2 discloses a forest fire online recognition device based on CN and CapsNet, which is the virtual device of the above-mentioned embodiment, please refer to Figure 4 shown, which includes:

[0087] Selection module 210 is used to select forest fire images under different lighting conditions, and constructs an initial sample set of forest fire flames; said initial sample set includes positive samples and negative samples;

[0088] The obtaining module 220 is used to obtain the flame region image of each sample in the initial sample set, and construct a flame sample set; the flame region image corresponding to the positive sample is called a flame positive sample, and the flame region image corresponding to a negative sample is called a flame negative sample. sample;

[0089] Creation module 230, is used to create three-passage CapsNet network model, described three-passage CapsNet network model comprises three CapsNet networks and a total fully connected laye...

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Abstract

The invention discloses a forest fire identification method and device based on a CN and a three-channel capsule network. The identification method comprises the following steps: constructing an initial sample set of forest fire flames; acquiring a flame region image of each sample in the initial sample set, and constructing to form a flame sample set; creating a three-channel CapsNet network model according to the three-channel CapsNet network model; the method comprises the following steps: training a single CapsNet network through a Mnist data set; migrating parameters formed by training asingle CapsNet network into the three-channel CapsNet network model, wherein the parameters of a total full connection layer in the three-channel CapsNet network model are realized through random initialization; performing secondary training on the three-channel CapsNet network model through the flame sample set to form a final fire identification model; and constructing a principal component color space vector described by the flame sample set by applying a CN algorithm. According to the invention, the real-time performance and effectiveness of fire detection are improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a forest fire recognition method and device based on CN and three-channel capsule network. Background technique [0002] Forest fire is one of the factors that seriously affect the ecological environment. The harm it brings to the forest is destructive, and the harm it brings to the environment is also destructive. Once a forest fire occurs, it is very difficult to extinguish it. Therefore, timely warning of forest fires is extremely important. [0003] With the advancement of science and technology, the early warning of forest fires has made great progress. There are many forest fire detection methods, and there are many forest fire detection algorithms based on image recognition. Among them, there are a variety of algorithms based on color space fire detection and recognition algorithms. The color-based fire recognition algorithm cannot get rid of the inherent def...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/13G06V10/56G06N3/045G06F18/214Y02A40/28
Inventor 赵运基周梦林张楠楠范存良孔军伟刘晓光张新良
Owner HENAN POLYTECHNIC UNIV
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