This paper proposes a novel method to detect
fire and/or smoke in real-time by processing the video
data generated by an ordinary camera monitoring a
scene. The objective of this work is recognizing and
modeling fire shape evolution in stochastic visual
phenomenon. It focuses on detection of fire in image
sequences by applying a new hybrid algorithm that
depends on optimizing the back-propagation algorithm,
after canny edge detection, for determining the smoke
and fire boundaries. Another clue is used in the fire
detection algorithm that detects smoke and fire flicker
by analyzing the video in the wavelet domain. Color
variations in flame regions are detected by computing
the spatial wavelet transform of moving fire-colored
regions. Experimental results show that the proposed
algorithm is very successful in detecting fire and/or
smoke. |
