Real-time smoke detection using texture and color features

Yue Wang, Teck Wee Chua, Richard Chang, Nam Trung Pham

Abstract: This paper presents a real-time smoke detection algorithm. A modified Center Symmetric Local Ternary Pattern (CS-LTP) is proposed as the smoke texture descriptor. The change in background texture provides a means to differentiate between smoke and non-smoke region. Combined with the color information of smoke, our method is able to achieve real-time performance at minimum of 30 fps. The comparison with the state of art is presented as well. The experiment results show the proposed method can obtain good performance.