A Vision-Based Approach to Fire Detection. (18th September 2014)

• Record Type: Journal Article
• Authors: Gomes, Pedro; Santana, Pedro; Barata, José
• Is Part Of: International journal of advanced robotic systems. Volume 11:Number 9(2014)
• Publication Date: 2014-09-18
• Subjects: Vision Systems -- Fire Detection -- Smart Cameras -- Computer Vision -- Object Detection & Tracking; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.5772/58821
• Languages: English
• ISSNs: 1729-8806

Abstract

This paper presents a vision-based method for fire detection from fixed surveillance smart cameras. The method integrates several well-known techniques properly adapted to cope with the challenges related to the actual deployment of the vision system. Concretely, background subtraction is performed with a context-based learning mechanism so as to attain higher accuracy and robustness. The computational cost of a frequency analysis of potential fire regions is reduced by means of focusing its operation with an attentive mechanism. For fast discrimination between fire regions and fire-coloured moving objects, a new colour-based model of fire's appearance and a new wavelet-based model of fire's frequency signature are proposed. To reduce the false alarm rate due to the presence of fire-coloured moving objects, the category and behaviour of each moving object is taken into account in the decision-making. To estimate the expected object's size in the image plane and to generate geo-referenced alarms, the camera-world mapping is approximated with a GPS-based calibration process. Experimental results demonstrate the ability of the proposed method to detect fires with an average success rate of 93.1% at a processing rate of 10 Hz, which is often sufficient for real-life applications.