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Fire video image recognition method and system, computer equipment and storage medium

A video image and recognition method technology, applied in the field of computer vision, can solve the problems affecting the accuracy of the sensor, high cost, and high price of the sensor, to improve the detection efficiency and accuracy, solve the lack of lighting and shadows, and ensure the safety of personal and property. Effect

Active Publication Date: 2022-04-29
SOUTH CHINA UNIV OF TECH +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional fire detection technology has certain limitations: First, it is limited to a closed environment. If the physical characteristics change in a large area, the detection efficiency of the sensor is reduced, and the physical characteristics such as gas and particles are transmitted to the sensor. The time becomes longer as the distance increases, and the detection time becomes longer, making it impossible to broadcast in time; second, it is easily affected by the environment. Changes in environmental factors such as rain, snow, and wind speed will affect the physical characteristics of the fire scene, thereby affecting The accuracy of sensor detection; third, the cost is high, the price of the sensor is high, and it is easy to be corroded, aged or even damaged
However, the current artificial intelligence-based fire detection technology model is complex, the number of parameters is too large, and the detection efficiency is low, which is not conducive to the rapid detection of fire.

Method used

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  • Fire video image recognition method and system, computer equipment and storage medium
  • Fire video image recognition method and system, computer equipment and storage medium
  • Fire video image recognition method and system, computer equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] Such as figure 1 As shown, the present embodiment provides a fire video image recognition method, the method includes the following steps:

[0073] S101. Obtain a data set.

[0074] This embodiment collects flame and non-fire videos through the network, and then performs frame processing (with 12 frames as a unit) on the collected flame and non-fire videos through the opencv library, so as to obtain labeled fire and non-fire video image dataset.

[0075] Further, in this embodiment, a script is used to divide the above data set into a training set and a test set, and data enhancement is performed on the training set, wherein the data enhancement includes random rotation, mirroring and random cropping.

[0076] S102. Construct a convolutional neural network.

[0077] Such as figure 2 As shown, the convolutional neural network in this embodiment includes one layer of input layer, one layer of module A, three layers of module B, two layers of module C, two layers of ...

Embodiment 2

[0105] Such as Figure 9 As shown, the present embodiment provides a fire video image recognition system, the system includes a first acquisition unit 901, a construction unit 902, a training unit 903, a second acquisition unit 904 and a recognition unit 905, and the specific functions of each unit are as follows:

[0106] The first acquisition unit 901 is configured to acquire a data set, the data set is a fire and non-fire video image data set;

[0107] The construction unit 902 is used to construct a convolutional neural network, and the convolutional neural network includes one layer of input layer, one layer of module A, three layers of module B, two layers of module C, two layers of 1×1 convolutional block A, four layer max pooling layer, one layer adaptive average pooling layer, one layer flatten layer, layer dropout layer, a fully connected layer, and a softmax classification layer;

[0108] The training unit 903 is used to use the data set to train the convoluti...

Embodiment 3

[0113] Such as Figure 10 As shown, this embodiment provides a computer device, which includes a processor 1002 connected through a system bus 1001 , a memory, an input device 1003 , a display device 1004 and a network interface 1005 . Wherein, the processor 1002 is used to provide calculation and control capabilities, and the memory includes a non-volatile storage medium 1006 and an internal memory 1007, the non-volatile storage medium 1006 stores an operating system, a computer program and a database, and the internal memory 1007 is The operating system in the nonvolatile storage medium 1006 and the operation of the computer program provide an environment, and when the computer program is executed by the processor 1002, the fire video image recognition method of the above-mentioned embodiment 1 is realized, as follows:

[0114] Obtaining a data set, the data set is a video image data set of fire and non-fire;

[0115] Construct a convolutional neural network, the convolutio...

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Abstract

The invention discloses a fire video image recognition method and system, computer equipment and a storage medium, and the method comprises the steps: obtaining a data set which is a fire and non-fire video image data set; constructing a convolutional neural network; training the convolutional neural network by using the data set to obtain a fire video image recognition model; obtaining a to-be-recognized video, and performing framing processing on the to-be-recognized video to obtain a to-be-recognized video image; and inputting the to-be-identified video image into the fire video image identification model to realize fire video image identification. The method can reduce the parameter quantity of the network model, improves the detection efficiency and accuracy of the network model, achieves the quick recognition of the fire video image, can timely discover the fire hazard, and guarantees the personal and property safety.

Description

technical field [0001] The invention relates to a fire video image recognition method, system, computer equipment and storage medium, belonging to the field of computer vision. Background technique [0002] With the improvement of our country's economic and technological level, the population is increasing, and the buildings are increasing and dense. The continued use of electricity and fuel increases the risk of fire, as does the damage caused by it. Fire not only causes social economic losses, but also endangers the safety of the public. Therefore, it is necessary to conduct special research on fire detection technology, so that it can identify the fire when the fire first ignites, and reduce the loss caused by the fire as much as possible. , to protect people's safety. [0003] Traditional fire detection technologies mainly include smoke detection, temperature detection, light detection and gas detection, which mainly identify the occurrence of fire based on the physica...

Claims

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Application Information

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IPC IPC(8): G06V20/52G06V10/44G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06N3/048G06N3/045G06F18/241G06F18/2415
Inventor 柯峰方恩权杨利萍庄泽升彭东亮马跃何冬冬
Owner SOUTH CHINA UNIV OF TECH
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