A Forest Fire Detection System: The Meleager Approach

Forest fires cause immeasurable damages to indispensable resources for human survival, destroy the balance of earth ecology and worst of all they frequently cost human lives. In recent years, early fire detection systems have been emerged to provide monitoring and prevention of the disasterous forest fires. Among them, the Meleager1 system aims to offer one of the most advanced and integrated technology solutions for fire protection worldwide by integrating several innovative features. This paper outlines one of the major components of the Meleager system, that is the visual fire detection sybsystem. Ground based visible range PTZ cameras monitor the area of interest and a low level decision fusion scheme is used to combine individual decisions of noumerous fire detection algorithms. Personalized alerts and induced feedback is used to adapt the detection process and improve the overall system performance.

[1]  Hongcheng Wang,et al.  Video-based Smoke Detection : Possibilities , Techniques , and Challenges , 2007 .

[2]  Zhang Yongming,et al.  Video Fire Smoke Detection Using Motion and Color Features , 2010 .

[3]  Alex Pentland,et al.  Pfinder: real-time tracking of the human body , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[4]  Kazuhiko Sumi,et al.  Background subtraction based on cooccurrence of image variations , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[5]  Turgay Çelik,et al.  Fire detection using statistical color model in video sequences , 2007, J. Vis. Commun. Image Represent..

[6]  Chao-Ho Chen,et al.  An early fire-detection method based on image processing , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[7]  Alex Pentland,et al.  A Bayesian Computer Vision System for Modeling Human Interactions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Zhiyong Yuan,et al.  Color Based Segmentation and Shape Based Matching of Forest Flames from Monocular Images , 2009, 2009 International Conference on Multimedia Information Networking and Security.

[9]  Hu Peng,et al.  Technique for automatic forest fire surveillance using visible light image , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[10]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[11]  Aníbal Ollero,et al.  An Intelligent System for False Alarm Reduction in Infrared Forest-Fire Detection , 2000, IEEE Intell. Syst..

[12]  Begoña C. Arrue,et al.  Computer vision techniques for forest fire perception , 2008, Image Vis. Comput..

[13]  Alex Pentland,et al.  A Bayesian Computer Vision System for Modeling Human Interaction , 1999, ICVS.

[14]  Bohyung Han,et al.  SEQUENTIAL KERNEL DENSITY APPROXIMATION THROUGH MODE PROPAGATION: APPLICATIONS TO BACKGROUND MODELING , 2004 .

[15]  Andrei B. Utkin,et al.  Detection of small forest fires by lidar , 2002 .

[16]  Turgay Çelik,et al.  Fire and smoke detection without sensors: Image processing based approach , 2007, 2007 15th European Signal Processing Conference.

[17]  Hiroaki Kuze,et al.  Detection of biomass burning smoke in satellite images using texture analysis , 2002 .

[18]  Alex Pentland,et al.  Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  A. Enis Çetin,et al.  Computer vision based method for real-time fire and flame detection , 2006, Pattern Recognit. Lett..

[20]  Dengyi Zhang,et al.  Contour Based Forest Fire Detection Using FFT and Wavelet , 2008, 2008 International Conference on Computer Science and Software Engineering.

[21]  Feiniu Yuan,et al.  A fast accumulative motion orientation model based on integral image for video smoke detection , 2008, Pattern Recognit. Lett..

[22]  Ebroul Izquierdo,et al.  Efficient visual fire detection applied for video retrieval , 2008, 2008 16th European Signal Processing Conference.

[23]  Kasim Tasdemir,et al.  Video based wildfire detection at night , 2009 .

[24]  Miguel Garcia,et al.  A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification , 2009, Sensors.

[25]  Xiaojun Qi,et al.  A computer vision-based method for fire detection in color videos , 2009 .

[26]  A. Enis Çetin,et al.  Flame detection in video using hidden Markov models , 2005, IEEE International Conference on Image Processing 2005.

[27]  W. Eric L. Grimson,et al.  Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[28]  Larry S. Davis,et al.  Non-parametric Model for Background Subtraction , 2000, ECCV.

[29]  Takeo Kanade,et al.  A System for Video Surveillance and Monitoring , 2000 .

[30]  A. Enis Çetin,et al.  Contour based smoke detection in video using wavelets , 2006, 2006 14th European Signal Processing Conference.

[31]  A. Cetin,et al.  Video Based Wild Fire Detection at Night , 2009 .