A novel video-based smoke detection method using image separation

Authors

Hongda Tian, University of WollongongFollow
Wanqing Li, University of WollongongFollow
Lei Wang, University of WollongongFollow
Philip O. Ogunbona, University of WollongongFollow

RIS ID

71282

Publication Details

Tian, H., Li, W., Wang, L. & Ogunbona, P. O. (2012). A novel video-based smoke detection method using image separation. ICME 2012: IEEE International Conference on Multimedia and Expo (pp. 532-537). IEEE Xplore: IEEE.

Abstract

In the state-of-the-art video-based smoke detection methods, the representation of smoke mainly depends on the visual information in the current image frame. In the case of light smoke, the original background can be still seen and may deteriorate the characterization of smoke. The core idea of this paper is to demonstrate the superiority of using smoke component for smoke detection. In order to obtain smoke component, a blended image model is constructed, which basically is a linear combination of background and smoke components. Smoke opacity which represents a weighting of the smoke component is also defined. Based on this model, an optimization problem is posed. An algorithm is devised to solve for smoke opacity and smoke component, given an input image and the background. The resulting smoke opacity and smoke component are then used to perform the smoke detection task. The experimental results on both synthesized and real image data verify the effectiveness of the proposed method. 2012 IEEE.