Publications

Abstract : Computer Vision based approaches is a significant area of research area in detecting and segmenting the anomalies in a building environment. Vision sensor approaches influence automation in detection and localization. Existing fire detection framework has overcome the constraints in conventional approaches such as threshold limits, environmental pollution, proximity to fire, etc. In this paper we propose a new method for fire detection in smart building with a vision sensor that is inspired by computer vision approaches. This proposed method identifies fire pixel using three steps: the first step is based on Gaussian probability distribution; the second one uses a hybrid background subtraction method and the third is based on temporal variation. These three steps are essentially used to address distinct challenges such as Gaussian noise in frames and different resolution of videos. Experimental results show good detection accuracy for video frames under various illuminations and are robust to noise like smoke.