Flame Detection In Videos Based On Spatio-temporal Visual Saliency

In modern time, the fire is one of the most frequent and most common disasters, it directly endangers the safety of human life and property. Constant and effective warning of fire has become a major concern of the society. Traditional fire detectors has low cost and high efficiency, but also has many disadvantages, especially in real-time performance, detection range and the robustness. With the development of video monitoring equipment and the computer vision and image processing technology, the fire detection technology based on visual features has become the focus.In this paper, the visual salient features of the flame were studied, and the advantages and disadvantages of the domestic and foreign video fire detection technology were compared and analyzed. According to a study of the performance in the flame combustion process, the idea of visual outstanding in computer vision was introduced, and the temporal-spatial visual model was integrated. In the model, the characteristics of flame in space and time were studied, and the detection of flame was finally realized by using the bionic visual attention mechanism.Color, brightness and texture are all of spatial salient features of flame. The Lab color space which is similar with human visual was introduced to define flame color saliency and preprocessed by threshold segmentation and Gaussian filter. Then the flame color saliency was obtained through difference algorithm. The brightness saliency map was acquired by combining the center-surround difference and vertical gray-level integral projection method.With the linear fusion of the flame color and intensity saliency, flame spatial saliency map was got by dispersion texture feature. In the article, an improved motion detection algorithm was aimed at making up the shortcoming of common flame moving target detection.According to the new algorithm, the moving regions can be tested on multiple image sequence, and the flame time saliency map can be constructed under the characteristics of movement cumulative and color, combining the advantages of background updating methodand frame difference algorithm. Integrated with the time saliency map and spatial saliency map, the flame can be judged and identified ultimately through the main migration orientation.In order to verify the effective of the proposed method, a large number of different scenarios videos were tested. The experimental results proved that the proposed method can detect the flame in video accurately, real-time and effectively, and has strong anti-interference ability.