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Forest fire identification method and device based on interpolated CN and capsule network

A forest fire and identification method technology, applied in the field of forest fire identification, can solve the problems of high false alarm rate and inconsistent scale of fire detection algorithm

Active Publication Date: 2020-06-16
HENAN POLYTECHNIC UNIV
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AI Technical Summary

Problems solved by technology

[0004]In order to overcome the influence of light transformation in the process of flame detection based on color space, which caused the defect of high false positive rate of fire detection algorithm based on color space description, the detection results When the image is input into the capsule network, the scale is inconsistent, and the impact of forced scale conversion on the depth features of the original image ensures the consistency of spatial features under different scale conditions. The invention provides a forest fire recognition method based on interpolation CN and capsule network and device

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  • Forest fire identification method and device based on interpolated CN and capsule network
  • Forest fire identification method and device based on interpolated CN and capsule network

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Embodiment 1

[0056] Embodiment 1 of the present invention discloses a forest fire identification method based on interpolation CN and capsule network, please refer to figure 1 As shown, it includes the following steps:

[0057] 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.

[0058] 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

[0083] 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 5 shown, which includes:

[0084] 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;

[0085] The standardization module 220 is configured to grayscale the color images of the flame regions of all samples in the initial sample set, perform continuous spatial domain interpolation on the grayscaled sample images to achieve scale standardization, and standardize the scale The collection of sample images after is called the flame sample collection;

[0086] The training module 230 is used to train the CapsNet network through the Mnist data set, and adopts the transfer learning method to carry out transfer learning to the trained...

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Abstract

The invention discloses a forest fire identification method based on an interpolated CN and a capsule network. The forest fire identification method comprises the following steps: constructing an initial sample set of forest fire flames; performing graying operation on the initial sample set, and performing continuous spatial domain interpolation on the grayed sample image to realize scale standardization; training the CapsNet network through a transfer learning method to form a final fire identification model; constructing a principal component color space vector described by the flame sampleset by applying a CN algorithm; collecting a target image, and determining a suspected flame area; extracting a suspected flame image and graying, and performing scale standardization by applying a continuous spatial linear interpolation method; and inputting the target standardized image into a fire identification model to obtain a final identification result. The invention further discloses a forest fire identification device based on the interpolated CN and the capsule network. 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 capsule network based on linear interpolation in continuous space domain. 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 a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08G06T3/40G06T5/30G06T7/11G08B17/00
CPCG06N3/08G06T7/11G06T5/30G06T3/4007G08B17/005G06T2207/10024G06T2207/30188G06V20/38G06V10/56G06N3/045G06F18/2135G06F18/241G06F18/214Y02A40/28
Inventor 赵运基周梦林张楠楠魏胜强刘晓光孔军伟
Owner HENAN POLYTECHNIC UNIV
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