Research on Automatic Positioning Algorithm of Fire Point by Video Image in Intelligent Forest
International Journal of Information and Communication Sciences
Volume 4, Issue 1, March 2019, Pages: 18-23
Received: Apr. 21, 2019;
Accepted: May 28, 2019;
Published: Jun. 12, 2019
Views 634 Downloads 99
Gaohe Li, School of Economic Management, Xi'an Shiyou University, Xi’an, China
Yanli Zhang, International Business School, Shaanxi Normal University, Xi’an, China
Based on the digital video monitoring system in smart forest, the automatic positioning algorithm of forest fire is studied by using camera calibration technique and spatial stereo analysis. Using the method of exhaustive search and dichotomy, the location of the fire point on the terrain profile is determined by DEM model and using the principle of stereoscopic geometry. According to the characteristics of the forest terrain changes, using translation methods of the camera optical axis in the space, the mapping relationship between the plane pixel coordinates and the spatial coordinates is established. The research simplifies the algorithm. It reduces the complexity of the algorithm, reduces the intermediate calculation link, and avoids the cumulative error of multiple calculations, and improves the calculation accuracy. In the algorithm proposed in this paper, after the test of more than 40 groups of data (due to limited space, this article only lists 24 sets of data) in two geographical locations, the straight-line distance error of the two previous calculations of the fire location is within 95m, and the accuracy of the rotation Angle and pitch Angle is greatly improved. The actual application shows that the localization algorithm can meet the automatic positioning of forest fire point and is an important part of intelligent forest monitoring system.
Research on Automatic Positioning Algorithm of Fire Point by Video Image in Intelligent Forest, International Journal of Information and Communication Sciences.
Vol. 4, No. 1,
2019, pp. 18-23.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Zhuang Zhemin, Hailong Liao, et al. Study on the Location of Early Fire Source in Inclined Wind Field Based on Weighted Distance Difference Method. Journal of Safety and Environment, 2011, vol. 11 (3): pp. 177-181
Wang S, BERENTSEN M, and KAISER T. Signal Processing for Fire Location Using Temperature Sensor Arrays. Fire Safety Journal, 2005, vol. 40 (8): pp. 689-697
Zhemin Zhuang, XinFeng Zhang, Kalin Li, et al. Method Research Fire Source Locaion Based on Planar Circluar Sensor Arrays. Chinese Journal of Sensors and Actuators. 2009, vol. 22 (8): pp. 1208-1212
Guangqun Yang, Ning Han. Study on Forest Fire Location Method Based on Camera Calibration Technology. Journal of Safety and Environment, 2013, vol. 13 (1): pp. 215-219.
Zhemin Zhuang, Hailong Liao, Shengqiang Huang, et al. On the Early Fire Source Locating Method Base on the Weighted Differential Distance Approach in the Skew Wind Field. Journal of Safety and Environment, 2011, vol. 11 (3): pp. 177-181.
Maolin Qiu, Songde Ma, Yi Li. Overview of Camera Calibration for Computer Vision. Acta Automatica Sinica, 2000, vol. 26 (11): pp. 43-55
Lifan Fei. Establishment of Digital Ground Model (DTM) and Its Application in Agricultural Planning. Regional Research and Development, 1988, 7 (4): pp. 42-43
Jian Zhang, Guangqun Yang, Ning Han GIS- Based Positioning Methods in Video Monitoring of Forest Fires. Forestry Machinery & Woodworking Equipment, 2009, vol. 36 (5): pp. 24-26.
Shouyi Lu, Xiaoming Tang, Shengguo Wang. A Tutorial on the Use of Geographic Information Systems. China Forestry Press. Beijing, China, 1998. p152.
Jianmin Yin. Research on Satellite Remote Sensing Fire Location Algorithm under ArcInfo. Nanjing Meteorological Journal, 2004, vol. 27 (5): pp. 688- 694.
Survey Adjustment Group, School of Surveying and Mapping, Wuhan University. Error Theory and Basis of Measurement Adjustment. Wuhan: Wuhan University Press, 2003. pp. 207.
Andrei B. Utkin, Armando Fernandes, Fernando Simoes, Alesander Lavrov and Rui Vilar. Feasibility of Forest - Fire Smoke Detection Using Lidar. International Journal of Wildland Fire, 2003, (12): pp. 159- 166.
Morsdorf, F., Meier, E., K#tz, B., Itten, K. I., Dobbertin, M., Allg$wer, B. LIDAR - Based Geometric Reconstruction of Boreal Type Forest Stands at Single Tree Level for Forest and Wildland Fire Management. Remote Sensing of Environment, 2004, 92 (3): pp. 353- 362.
Jian Zhang, Guangqun Yang, Ning Han, Yi Liang. Research on Forest Fire Location Algorithm Based on Video Monitoring System. Journal of Safety and Environment, 2009, Beijing, China, vol. 9 (1): pp. 127-130.
Qifeng Yu, Yang Shang. Principle and Application Research of Photogrammetry. Science Press, Beijing, China, 2009: pp. 23-25.