Adaptive estimation of visual smoke detection parameters based on spatial data and fire risk index

Standard wildfire smoke detection systems detect fires using remote cameras located at observation posts. Images from the cameras are analyzed using standard computer vision techniques, and human intervention is required only in situations in which the system raises an alarm. The number of alarms depends largely on manually set detection sensitivity parameters. One of the primary drawbacks of this approach is the false alarm rate, which impairs the usability of the system. In this paper, we present a novel approach using GIS and augmented reality to include the spatial and fire risk data of the observed scene. This information is used to improve the reliability of the existing systems through automatic parameter adjustment. For evaluation, three smoke detection methods were improved using this approach and compared to the standard versions. The results demonstrated significant improvement in different smoke detection aspects, including detection range, rate of correct detections and decrease in the false alarm rate.

[1]  Yuan-Fang Wang,et al.  Smoke Detection in Video , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[2]  Jesús San-Miguel-Ayanz,et al.  Towards a coherent forest fire information system in Europe: the European Forest Fire Information System (EFFIS). , 2002 .

[3]  Amel Benazza-Benyahia,et al.  Early smoke detection in forest areas from DCT based compressed video , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).

[4]  Zhang Jiquan,et al.  GIS-based risk assessment of grassland fire disaster in western Jilin province, China , 2009 .

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

[6]  H. Maruta,et al.  Smoke detection in open areas using its texture features and time series properties , 2009, 2009 IEEE International Symposium on Industrial Electronics.

[7]  Mariko Nakano-Miyatake,et al.  Improvement of a Video Smoke Detection Based on Accumulative Motion Orientation Model , 2011, 2011 IEEE Electronics, Robotics and Automotive Mechanics Conference.

[8]  Xu Dong,et al.  Forest fire risk zone mapping from satellite images and GIS for Baihe Forestry Bureau, Jilin, China , 2005, Journal of Forestry Research.

[9]  S. Mukherjee,et al.  Forest fire risk zone mapping from satellite imagery and GIS , 2002 .

[10]  Josip Maras,et al.  Vision based wildfire and natural risk observers , 2012, 2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA).

[11]  Hongmei Yan,et al.  Smoke detection based on multi-feature fusion , 2012 .

[12]  Wageeh Boles,et al.  Texture Classification Using Multiple Wavelet Analysis , 2002 .

[13]  Jian Wang,et al.  An early smoke detection system based on increment of optical flow residual , 2012, 2012 International Conference on Machine Learning and Cybernetics.

[14]  A. Enis Çetin,et al.  Online Adaptive Decision Fusion Framework Based on Entropic Projections onto Convex Sets with Application to Wildfire Detection in Video , 2011, ArXiv.

[15]  Zhengguang Xu,et al.  Automatic Fire Smoke Detection Based on Image Visual Features , 2007, 2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007).

[16]  ByoungChul Ko,et al.  Wildfire smoke detection using spatiotemporal bag-of-features of smoke , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

[17]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[18]  Tzu-Hsin Kuo,et al.  Real-time video-based fire smoke detection system , 2009, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[19]  Simone Calderara,et al.  Reliable smoke detection in the domains of image energy and color , 2008, 2008 15th IEEE International Conference on Image Processing.

[20]  Maja Stula,et al.  Intelligent forest fire monitoring system , 2012, Inf. Syst. Frontiers.

[21]  Li Ma,et al.  Fire Smoke Detection in Video Images Using Kalman Filter and Gaussian Mixture Color Model , 2010, 2010 International Conference on Artificial Intelligence and Computational Intelligence.

[22]  Vincenzo Piuri,et al.  Wildfire smoke detection using computational intelligence techniques , 2011, 2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings.

[23]  Ming Li.  Correspondence Analysis Between The Image Formation Pipelines of Graphics and Vision , 2001 .

[24]  Janne Heikkilä,et al.  Geometric Camera Calibration Using Circular Control Points , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Darko Stipanicev,et al.  Visual spatial-context based wildfire smoke sensor , 2012, Machine Vision and Applications.

[26]  ByoungChul Ko,et al.  Forest Smoke Detection Using CCD Camera and Spatial-temporal Variation of Smoke Visual Patterns , 2011, 2011 Eighth International Conference Computer Graphics, Imaging and Visualization.

[27]  Yu Cui,et al.  An Early Fire Detection Method Based on Smoke Texture Analysis and Discrimination , 2008, 2008 Congress on Image and Signal Processing.

[28]  A. Enis Çetin,et al.  Entropy-Functional-Based Online Adaptive Decision Fusion Framework With Application to Wildfire Detection in Video , 2012, IEEE Transactions on Image Processing.

[29]  Ricardo Carmona-Galán,et al.  A vision-based monitoring system for very early automatic detection of forest fires. , 2008 .

[30]  Vincenzo Piuri,et al.  Wildfire Smoke Detection Using Computational Intelligence Techniques Enhanced With Synthetic Smoke Plume Generation , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[31]  Darko Stipaničev,et al.  Wildfire smoke-detection algorithms evaluation , 2011 .

[32]  Wenguo Weng,et al.  GIS-Based Forest Fire Risk Assessment and Mapping , 2011, 2011 Fourth International Joint Conference on Computational Sciences and Optimization.

[33]  Fang Jun,et al.  Texture Analysis of Smoke for Real-Time Fire Detection , 2009, 2009 Second International Workshop on Computer Science and Engineering.

[34]  Jing Yang,et al.  Visual-Based Smoke Detection Using Support Vector Machine , 2008, 2008 Fourth International Conference on Natural Computation.

[35]  David R. Brillinger,et al.  Probability based models for estimation of wildfire risk , 2004 .

[36]  Stathes Hadjiefthymiades,et al.  Multisensor data fusion for fire detection , 2011, Inf. Fusion.

[37]  ByoungChul Ko,et al.  Wildfire smoke detection using temporospatial features and random forest classifiers , 2012 .

[38]  Ali Rafiee,et al.  Fire and smoke detection using wavelet analysis and disorder characteristics , 2011, 2011 3rd International Conference on Computer Research and Development.

[39]  Stephen Brooks,et al.  Multilayer hybrid visualizations to support 3D GIS , 2008, Comput. Environ. Urban Syst..

[40]  Han Ning,et al.  Design of automatic forest fire positioning system based on video monitoring system , 2010, 2010 Second IITA International Conference on Geoscience and Remote Sensing.

[41]  Jong-Myon Kim,et al.  An early smoke detection system based on motion estimation , 2010, International Forum on Strategic Technology 2010.

[42]  Darko Stipaničev,et al.  HISTOGRAM-BASED SMOKE SEGMENTATION IN FOREST FIRE DETECTION SYSTEM , 2009 .

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

[44]  A. Enis Çetin,et al.  Wavelet based real-time smoke detection in video , 2005, 2005 13th European Signal Processing Conference.

[45]  Jürgen Döllner,et al.  An object-oriented approach for integrating 3D visualization systems and GIS , 2000 .

[46]  B. Matthews.  Comparison of the predicted and observed secondary structure of T4 phage lysozyme. , 1975, Biochimica et biophysica acta.

[47]  Han Ning,et al.  A Smoke Detection Algorithm Based on Discrete Wavelet Transform and Correlation Analysis , 2012, 2012 Fourth International Conference on Multimedia Information Networking and Security.

[48]  Andrew A. Lovett,et al.  Rural landscape visualisation from GIS databases: a comparison of approaches, options and problems , 2002 .

[49]  Chao-Ho Chen,et al.  The smoke detection for early fire-alarming system base on video processing , 2006, 2006 International Conference on Intelligent Information Hiding and Multimedia.

[50]  Maja Štula,et al.  Advanced automatic wildfire surveillance and monitoring network , 2010 .