Citation

Arrue BC, Ollero A, Martínez-de-Dios JR. IEEE Intell. Syst. Appl. 2000; 15(3): 64-73.

Copyright

(Copyright © 2000)

DOI

10.1109/5254.846287

PMID

unavailable

Abstract

Forest fires cause many environmental disasters, creating economical and ecological damage as well as endangering people's lives. Heightened interest in automatic surveillance and early forest-fire detection has taken precedence over traditional human surveillance because the latter's subjectivity affects detection reliability, which is the main issue for forest-fire detection systems. In current systems, the process is tedious, and human operators must manually validate many false alarms. Our approach, the False Alarm Reduction system, proposes an alternative real-time infrared-visual system that overcomes this problem. The FAR system consists of applying new infrared-image processing techniques and artificial neural networks (ANNs), using additional information from meteorological sensors and from a geographical information database, taking advantage of the information redundancy from visual and infrared cameras through a matching process, and designing a fuzzy expert rule base to develop a decision function. Furthermore, the system provides the human operator with new software tools to verify alarms

Language: en