Study On Flame Video Detection Technology Of Moving Tunnel Fire Based On Image Features

The continuous construction of tunnel traffic is outstanding contribution to shorten the distance and improve traffic efficiency. While, with increasing of tunnel traffic speed and traffic density, tunnel fire accidents are more frequent, especially accidents caused by vehicles. As a semi-enclosed and limited space, it is dusty,humidity and large vertical wind in tunnel. The traditional detection technology is not applicable in tunnel. In this paper, the video flame detection technology for moving tunnel fire is investigated.Based on the experiment, flame video data of moving tunnel fire was collected. Meanwhile, video data of stationary tungsten and lamp was obtained, in order to compare the flame video data. According to flame color and brightness information, a background update model is established for tunnel. the model is effective to remove a small amount of reflected sunlight and flame. However, stationary tungsten and lamp are identified as candidate region of the flame.Therefore, based on the candidate region, the flame continuous shake and the changing number of the cusp is investigated, which is different from the stable of the edge lights. The Harris algorithm is adopted to extract the flame cusp. Then, changes in the number of frames cusp is investigated and adopted to identify the flame image and the image of non-flame.As the flame flicker frequency related size of fire, it is difficult to recognize the flame image, based on the flame flicker frequency directly. It is established based on the flame flickering, as a supplementary criterion. Flame area oscillations over time, which are different from stationary tungsten and lamp. Flame area of stationary tungsten is constant; and flame area of lamp is increasing. By studying each of the three consecutive frames in the two adjacent frames, the product of the difference between the image areas is set, in order to identify flame image and light image.