Approach to Detecting Forest Fire by Image Processing Captured from IP Cameras
Keywords:Forest fire, Smoke and Fire Detection, DCT, IP Camera, Images Processing
In this paper, the results show an algorithm to detect the presence of smoke and flame using image sequences captured by Internet Protocol (IP) cameras is represented. The important characteristics of smoke such as color, motion and growth properties are employed to detect fire. For the efficient smoke and fire detection in the captured images by the IP camera, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational weigh, avoiding a complete decoding process required for algorithms that operate in spatial domain. In order to assess the possibility and the accuracy of proposed algorithm, the author used the video sequences which are captured by IP camera from control forest fire at different spatial location and levels of fire intensity. Evaluation results illustrated the efficiency of the proposed algorithm in effectively detecting forest fires with accuracy at 97%.
(1) Chen, T.; Yin, S; Huang, Y.; Ye, Y. The Smoke Detection for Early Fire-Alarming System Based on Video Processing. In Proceedings of International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Pasadena, CA, USA, 18-20 December 2006.
(2) Leonardo Millan-Garcia, Gabriel Sanchez-Perez, Mariko Nakano, Karina Toscano-Medina, Hector Perez-Meana and Luis Rojas-Cardenas, “An Early Fire Detection Algorithm Using IP Cameras” in Sensors 2012, 12, 5670-5686, pp. 5670-5686.
(3) Schneiderman, R. Trends in Video Surveillance Given DSP an Apps Boost. IEEE Sign. Process. Mag. 2010, 6, 6-12.
(4) Turgay Çelik, Hüseyin Özkaramanlı, and Hasan Demirel, “Fire and smoke detection without sensors: Image processing based approach” in 15th European Signal Processing Conference (EUSIPCO 2007), Poznan, Poland, September 3-7, 2007, pp. 1794-1798.
(5) Yuan F. Video-Based Smoke Detection with Histogram Sequence of LBP and LBPV Pyramids. Fire Safety J. 2011, 46, 132-139.
(6) Yu C.; Faon J.; Wang J.; Zhang Y.; State K. Video Fire Smoke Detection Using Motion and Color Features. Fire Technol. 2010, 46, 651-663.