Fire detection with a frame-less vision sensor working in the NIR band

Abstract

This paper draws the attention of the community about the capabilities of an emerging generation of bio-inspired vision sensors to be used in fire detection systems. Their principle of operation will be described. Moreover experimental results showing the performance of an eventbased vision sensor will be provided. The sensor was intended to monitor flames activity without using optic filters. In this article, we will also extend this preliminary work and explore how its outputs can be processed to detect fire in the environment. IntroductionInfrared cameras can easily detect fire and hot spots. Unfortunately, they are expensive, difficult to handle, and fragile (Briz et al. 2003). For this reason, CMOS cameras are still preferred for some applications where it is not strictly necessary operating in the whole infrared band, (Cheon et al. 2009, Naoult et al. 2007, Bendiscio et al. 1998, Fernandez-Berni et al. 2012. Silicon can detect Near Infrared Radiation (NIR) within the band [700 1,100] nm. This property can be exploited to monitor flame and fire activity.Flames have a very characteristic oscillatory behavior. They flicker with certain frequency components that depend on their nature. The study of these frequency components is interesting for industrial processes and applications. Traditionally CMOS cameras with NIR filters have been employed (Yan et al. 2006). As an alternative to this traditional approach, recently we proposed an bio-inspired event-based system to monitor flame activity without using optic filters (Leñero-Bardallo et al. 2013). The idea behind this method was to compare the photocurrents of stacked photodiodes at different depths. The top one was more sensitive to shorter wavelengths and the bottom one was more sensitive to longer wavelengths, having a very good sensitivity within the NIR band. Just comparing the difference between their photocurrents, we were able to determine if the incident radiation was within the NIR band without optic filters. Moreover, we could process with a real-time algorithm the temporal variations of the NIR levels in the visual scene provoked by flames and compute their frequency components values. This paper studies how the prior work to monitor flame activity could be extended to detect fire in the environment and emit an alarm in case. We will show that the previously implemented algorithm outputs can be processed to detect fire with a low computational load. Up