Smoke detection using boundary growing and moments

In this paper, we propose a smoke detection method using block based subtraction, boundary region growing and moments in outdoor video sequences. Our proposed method is composed of three steps; the initial change area segmentation step, the boundary finding and expanding step, and the smoke classification step. In the first step, we use a background subtraction to detect changed areas in the current input frame against the background image. In the second step, we find boundaries of the changed areas using labeling algorithm and expand the boundaries to their neighbors using the boundary region growing algorithm. In the final step, ellipses of the boundaries are estimated using moments. We classify whether the boundary is smoke by using the temporal information.