A novel video-based smoke detection method based on color invariants

In this paper, we address the issue of designing a smoke detector robust to illumination variations. Our contribution consists in resorting to color invariants as salient smoke features. More precisely, the proposed detector employs consecutively of an illumination invariant color representation, a photometric gain based background subtraction, a chrominance detection and a smoke identification based on two invariant color descriptors. The experimental results show that the proposed method can effectively detect smoke with robustness to illumination changes and noises, frequently encountered in wildfire video-surveillance environments.