ICUAS'17 Paper Abstract

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Paper WeC4.2

Yuan, Chi (Concordia University), Liu, Zhixiang (Concordia University), Zhang, Youmin (Concordia University)

Fire Detection Using Infrared Images for UAV-Based Forest Fire Surveillance

Scheduled for presentation during the "UAS Applications - III" (WeC4), Wednesday, June 14, 2017, 17:00−17:20, Lummus Island

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on July 22, 2019

Keywords UAS Applications, Risk Analysis, Technology Challenges

Abstract

Unmanned aerial vehicle (UAV) based computer vision system, as a more and more promising option for forest fires surveillance and detection, is now widely employed. In this paper, an image processing method for the application to UAV is presented for the automatic detection of forest fires in infrared (IR) images. The presented algorithm makes use of brightness and motion clues along with image processing techniques based on histogram-based segmentation and optical flow approach for fire pixels detection. First, the histogram-based segmentation is used to extract the hot objects as fire candidate regions. Then, the optical flow method is adopted to calculate motion vectors of the candidate regions. The motion vectors are also further analyzed to distinguish fires from other fire analogues. Through performing morphological operations and blob counter method, a fire can be finally tracked in each IR image. Experimental results verified that the designed method can effectively extract and track fire pixels in IR video sequences.

 

 

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