Method and device for detecting flame

Abstract

The embodiment of the present invention discloses a method for detecting flames, the method comprising: obtaining a detection picture; inputting multiple detection pictures into a flame detection network, and obtaining a suspected flame area circled by a candidate frame on the detection picture ; The detection picture is cut according to the candidate frame, and deformed into a suspected flame picture of the same size; wherein, the flame detection network is a two-stage cascaded convolution that adds a self-variable convolution layer to the candidate area extraction layer network; the suspected flame picture is input into the 3D convolutional network, and the spatial features and low-order dynamic features of the suspected flame picture are extracted; the spatial features and low-order dynamic features are input into the cyclic neural network, and the extracted High-order dynamic features of the suspected flame picture, and determine whether there is flame in the suspected flame picture. Through the flame detection method provided in the embodiment of the present application, the flame in the detection picture can be identified more accurately and quickly.

Description

technical field [0001] The invention relates to the field of image detection, in particular to a method and device for detecting flames. Background technique [0002] With the rapid development of the economy, various high-level comprehensive construction groups continue to emerge. In high-rise buildings, due to dense population and concentrated property, the fire protection problem is also particularly prominent. Although there are mature flame detection methods now, such as smoke detectors, temperature detectors, and photosensitive detectors, the flames are detected using the characteristics of smoke, temperature, and light of flames. [0003] However, in comprehensive shopping malls, due to the large number of merchants, the back kitchens of catering merchants are relatively small and closed, and it is impossible to install smoke, temperature, and photodetectors. The intensity of the flame detection is still not up to the alarm levels of smoke, temperature, and photosen...

AI Technical Summary

Problems solved by technology

[0003] However, in comprehensive shopping malls, due to the large number of merchants, the back kitchens of catering merchants are relatively small and closed, and it is impossible to install smoke, temperature, and photodetectors. The intensity of the fire is still not up to the alarm level of smoke, temperature, and photosensitive detectors, which brings a certain degree of difficulty to flame detection.

As a result, the fire in the shopping mall is a big fire when it is discovered, and it is extremely difficult to extinguish the work, and the flow of people in the shopping mall is relatively large. Once a fire occurs, it is bound to cause greater casualties

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