Fire Detection Method Using CCTV-based Flame Features and Density-based Spatial Clustering

In this study, we propose fire detection method using CCTV-based flame features and density-based spatial clustering with noise (DBSCAN). To do this, first, the 1st candidate region using the color of the flame image is extracted and the 2nd candidate region using the high-frequency region and background removal is extracted. Next, the extracted 1st candidate region and 2nd candidate region are merged, and the clustering region is extracted using DBSCAN. And then, the method for judging flame and rhinitis through the number of blocks passing through the movement trajectory of the central point of the clustering region extracted using DBSCAN is proposed. Finally, the applicability of the method proposed in this paper is reviewed through experiments in indoor and outdoor environments. © 2022 Korean Institute of Electrical Engineers. All rights reserved.