Research on Forest Fire Recognition Based on Computer Vision Technology

Abstract

In order to solve the problems of high false alarm rate and poor real-time performance in forest fire monitoring system due to the large amount of sample data and multi dimension of forest fire behavior monitoring, a support vector machine algorithm based on computer vision was proposed for forest fire monitoring to improve the recognition accuracy and realize all-weather forest fire automatic monitoring and early warning. Firstly, the image is obtained for preprocessing, and whether there are pyrotechnic areas in the image is preliminarily identified; Then, the feature extraction of forest fire is carried out, the feature vector is generated by training samples, and the SVM algorithm based on radial basis kernel function and polynomial kernel function is used to identify the fireworks, which puts forward a new idea for the intelligent exploration of forest fire prevention equipment.