YOLOV3-based smoke and fire automatic detection and early warning method

Abstract

The invention provides a YOLOV3-based smoke and fire automatic detection and early warning method. The method comprises the steps of S1, constructing a sample set of a training detection model; S2, establishing a deep learning target detection network architecture based on YOLOV3; S3, configuring training parameters, and training a detection model; S4, acquiring to-be-detected image information; acquiring image frames of an on-site video picture from monitoring equipment on a to-be-detected site, and processing frame-by-frame images by utilizing an image preprocessing method; S5, detecting smoke and flame targets, and sending the video image frames processed in the step S4 into a pre-trained detection model in the step S3 for target detection, and outputting a detection result; S6, carrying out post-processing on a detection result; and S7, continuously analyzing the detection results of the multiple frames of images, confirming that the target is valid and outputting an alarm. According to the YOLOV3-based smoke and fire automatic detection and early warning method, second-level detection and alarm can be realized, the fire early warning time is greatly shortened, timely notification and timely rescue are realized, and fire spreading is effectively prevented.

Description

technical field [0001] The invention belongs to the technical field of video monitoring, and in particular relates to a method for automatic detection and early warning of fireworks based on YOLOV3. Background technique [0002] Pyrotechnics (smoke and flame) detection refers to the identification and location of pyrotechnics in surveillance video images, which is of great significance in the field of security surveillance. [0003] Fire is one of the most common and extremely harmful disasters, which often causes huge resource and property losses and may cause casualties. Therefore, for deep forests, unmanned warehouses, public facilities, flammable and explosive materials, Fireworks prevention and control and early warning have become the top priority. Timely early warning can quickly notify the on-duty personnel and assist firefighters to deal with the fire crisis in a timely manner, so as to prevent and avoid the sudden and spread of fire accidents as soon as possible, a...

AI Technical Summary

Problems solved by technology

The commonly used video detection method generally extracts the motion area of ​​the video image, and distinguishes it according to the characteristics of the RGB or HSV channel components of the flame area. This method has some effects on the discrimination of flames, but it cannot be used for smoke

There is also the use of block prediction of the image, using sliding windows of different sizes for region extraction, and then sending it to various CNNs (convolutional neural networks) for classification to determine whether it is flame or smoke, but this method has low efficiency and accuracy. It is not enough, and the position of the fireworks is not accurate enough, because the sliding window is pre-selected and the size and shape are fixed, while the shape of the smoke flame is not fixed

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