Video smoke detection using shape, color and dynamic features

Video smoke detection benefits life safety and environment protection. A method of video smoke detection using shape, color and dynamic texture features is presented in this paper. Firstly, an algorithm identifying cone geometry feature is used to distinguish conical region from dynamic regions. Secondly, conical regions are filtered by a color filtering algorithm to further test the candidate smoke region. Finally, a texture filtering algorithm is used to differentiate true smoke from candidate smoke regions. Experiments show that the proposed method is effective and it results in earlier and more reliable detection than the other two methods reported in the literature. The processing rate of the smoke detection method achieves 25 frames per second with an image size of 320x240 pixels.