Coverage analysis of moving object silhouettes in thermal and visual registered images

Fire is one of the leading hazards affecting everyday life around the world. The sooner the fire is detected, the better the chances are for survival. Today's fire alarm systems, such as video-based smoke detectors, however, still pose many problems. In order to accom- plish more accurate video-based smoke detection and to reduce false alarms, this paper proposes a multi-sensor smoke detector which takes advantage of the different kinds of information represented by visual and thermal imaging sensors. The detector analyzes the silhouette coverage of moving objects in visual and long-wave infrared registered (∼aligned) images. The registration is performed using a contour mapping algorithm which detects the rotation, scale and translation between moving objects in the multi-spectral images. The geometric parameters found at this stage are then further used to coarsely map the silhouette images and cov- erage between them is calculated. Since smoke is invisible in long-wave infrared its silhouette will, contrarily to ordinary moving objects, only be detected in visual images. As such,