Title :
A UAV vision system for airborne surveillance
Author :
Kontitsis, M. ; Valavanis, Kmon P. ; Tsourveloudis, N.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
fDate :
26 April-1 May 2004
Abstract :
The paper presents a machine vision system for aerial surveillance that can interpret and process data acquired by a UAV on-board infrared camera. System components include noise reduction, feature extraction, classification and decision-making. Decision-making is performed in terms of an alarm signal. The system has been configured for automatic fire detection applications where the alarm is set off in case of fire identification. Real time tests have been performed and the system has been tested producing sets of real images. Finally, a genetic algorithm was used to automatically define some of the system´s parameters.
Keywords :
aircraft; alarm systems; computer vision; decision making; feature extraction; genetic algorithms; remotely operated vehicles; surveillance; UAV vision system; airborne surveillance; alarm signal; decision-making; feature classification; feature extraction; genetic algorithm; machine vision system; noise reduction; onboard infrared camera; Cameras; Decision making; Feature extraction; Fires; Infrared surveillance; Machine vision; Noise reduction; Real time systems; System testing; Unmanned aerial vehicles;
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8232-3
DOI :
10.1109/ROBOT.2004.1307132
