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
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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.
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