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A flame detection method, device, electronic equipment and storage medium

A flame detection and flame technology, applied in the field of devices, electronic equipment and storage media, and flame detection methods, can solve the problems of low flame accuracy

Active Publication Date: 2021-01-05
成都睿沿科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the embodiments of the present application is to provide a flame detection method, device, electronic equipment, and storage medium for improving the low accuracy of flame detection

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  • A flame detection method, device, electronic equipment and storage medium
  • A flame detection method, device, electronic equipment and storage medium
  • A flame detection method, device, electronic equipment and storage medium

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Embodiment Construction

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0030]Before introducing the flame detection method provided by the embodiment of the present application, some concepts involved in the embodiment of the present application are first introduced:

[0031] Neural Network (Neural Network, NN), also known as Artificial Neural Network (ANN) or neural network, in the field of machine learning and cognitive science, is a kind of imitation of biological neural network (for example: the central nervous system of animals A mathematical or computational model of the structure and function of a system, which can be the brain, and an artificial neural network is used to estimate or approximate the function. A neural network model refers to a neural network model obtained after training an untrained neural network using preset training ...

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Abstract

The present application provides a flame detection method, device, electronic equipment and storage medium. The method includes: acquiring an image frame to be detected in video data; using a neural network model to predict the location area where the flame is located in the image frame to be detected; The area intercepts the corresponding area image from the image frame of the video data; uses the neural network model to extract the motion modal features of the multiple area images intercepted; uses the neural network model to predict the motion modal features, and obtains whether there is Detection results of real flames. In the above implementation process, the prediction is made based on the motion modal features extracted from the regional image of the flame location in the multi-frame video image, effectively utilizing the appearance features of the flame during motion and the dynamic motion feature information of multiple frames, so that Improved the accuracy of flame detection.

Description

technical field [0001] The present application relates to the technical fields of machine learning, target detection and video processing, and specifically relates to a flame detection method, device, electronic equipment and storage medium. Background technique [0002] At present, the main method for flame detection is to use a high-definition camera to obtain high-definition images, and use traditional image processing techniques to detect flames on the high-definition images, such as: filter the pixels in the high-definition image in color, time domain and space domain Wait for the operation. In the specific practice process, it is found that when traditional image processing technology is used to detect flames, it is easily interfered by other information in the environment. The other information here is specific such as: car lights, street lights and reflected lights, etc., using traditional images Processing technology can easily mistake light such as car lights, str...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/20G06K9/62
CPCG06V20/42G06V20/49G06V20/46G06V10/22G06F18/241G06F18/253
Inventor 曹亚周俊琨吉翔
Owner 成都睿沿科技有限公司