An intelligent system for false alarm reduction in infrared forest-fire detection
An intelligent system for false alarm reduction in infrared forest-fire detection
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DOI：
10.1109/5254.846287
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发表时间：
2000-05-01
期刊：
影响因子：
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通讯作者：
de Dios, JRM
中科院分区：
文献类型：
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作者：
Arrue, BC;Ollero, A;de Dios, JRM
森林火灾不仅造成经济损失和生态破坏，而且危及人民生命安全，是一种严重的环境灾害。对自动监视和早期森林火灾探测的高度兴趣已经优先于传统的人类监视，因为后者的主观性影响探测可靠性，这是森林火灾探测系统的主要问题。在当前的系统中，该过程是繁琐的，并且人类操作员必须手动验证许多假警报。我们的方法，虚警减少系统，提出了一种替代的实时红外视觉系统，克服了这个问题。FAR系统包括应用新的红外图像处理技术和人工神经网络，使用来自气象传感器和地理信息数据库的附加信息，通过匹配过程利用来自视觉和红外摄像机的信息冗余，以及设计模糊专家规则库以开发决策功能。此外，该系统为操作人员提供了新的软件工具来验证警报。
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.