Smoke detection in still video images using motion and color features

An efficient algorithm for smoke detection on sequences of color video images obtained from a still camera has been proposed. Our proposed algorithm in this research takes into account the dynamic and static properties of smoke and consists of different basic steps: segmentation of slow moving areas and pixels in the current input frame of the camera based on the adaptive background subtraction algorithm; The combination of slow moving areas with pixels in the form of bubbles and the classification of bubbles from the previous step. The adaptive background subtraction method has been used in the motion detection stage. The classification of bubbles is based on the calculation of optical flow, checking the Weber contrast, and also considers the initial path of smoke diffusion. Real sequences of security cameras have been used for smoke detection using our algorithm. A series of experimental results of video images are presented in this article.Translate