An early fire-detection method based on image processing

TLDR

The study proposes an early fire‑alarm method using video processing. It extracts fire and smoke pixels from RGB video by measuring chromaticity and disorder, then confirms fire by intensity, saturation, and growth dynamics. Experiments demonstrate the system achieves fully automatic fire surveillance with a lower false‑alarm rate, making it suitable for military, security, and commercial use.

Abstract

The paper presents an early fire-alarm raising method based on video processing. The basic idea of the proposed of fire-detection is to adopt a RGB (red, green, blue) model based chromatic and disorder measurement for extracting fire-pixels and smoke-pixels. The decision function of fire-pixels is mainly deduced by the intensity and saturation of R component. The extracted fire-pixels will be verified if it is a real fire by both dynamics of growth and disorder, and further smoke. Based on iterative checking on the growing ratio of flames, a fire-alarm is given when the alarm-raising condition is met. Experimental results show that the developed technique can achieve fully automatic surveillance of fire accident with a lower false alarm rate and thus is very attractive for the important military, social security, commercial applications, and so on, at a general cost.