Abstract: Automatic smoke detection in video plays a major role in the early detection and response of an unexpected fire hazard and the recognition of vehicle exhaust.One of the difficulties in smoke detection is eliminating the interference of moving objects with similar color as smoke effectively.In order to ensure the effectiveness and timeliness,the static statistical character of wavelet transforms was used,which can exclude the interferences such as cars or persons.At first,motion regions are obtained by background subtraction and then candidate smoke regions are extracted through histogram backproject method.At last,the wavelet transform is applied on the background and the corresponding video frame,and the difference between those two transformed images is yielded.According to the different statistical character of smoke and non-smoke,non-smoke is removed from the frame.The experimental results are impressive with limited false alarms,high accuracy and real-time capability.

Key words: Smoke detection,Background subtraction,Histogram backproject,Wavelet transformation