@article{ref1,
title="An intelligent system for false alarm reduction in infrared forest-fire detection",
journal="IEEE intelligent systems and their applications",
year="2000",
author="Arrue, Begoña C. and Ollero, Anibal and Martínez-de-Dios, José Ramiro",
volume="15",
number="3",
pages="64-73",
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<p /><p>Language: en</p>",
language="en",
issn="1094-7167",
doi="10.1109/5254.846287",
url="http://dx.doi.org/10.1109/5254.846287"
}