An intelligent system for false alarm reduction in infrared forest-fire detection

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