Real-time fire detection using enhanced color segmentation and novel foreground extraction

This paper proposes an effective real time fire detection technique, based on video processing. The proposed technique utilizes prominent features such as flame color information and spatiotemporal characteristics to identify fire areas. The initial stage of the work extracts fire colored pixels using a set of enhanced rules on RGB. Fire pixels are dynamic and to detect these moving pixels a novel method is proposed in this paper. The final verification is done by examining the area of the extracted regions. A harmful fire will grow over time, thus if the area happens to increase, the region under focus is declared as fire. Experimental results show that the model put forward outperforms other state of art models yielding an accuracy of 97.7%.