Smoke detection algorithm for intelligent video surveillance system

Abstract

An efficient smoke detection algorithm on color video sequences obtained from a stationary camera is proposed. Our algorithm considers dynamic and static features of smoke and is composed of basic steps: preprocessing; slowly moving areas and pixels segmentation in a current input frame based on adaptive background subtraction; merge slowly moving areas with pixels into blobs; classification of the blobs obtained before. We use adaptive background subtraction at a stage of moving detection. Moving blobs classification is based on optical flow calculation, Weber contrast analysis and takes into account primary direction of smoke propagation. Real video surveillance sequences were used for smoke detection with utilization our algorithm. A set of experimental results is presented in the paper.

Keywords

• smoke detection
• video sequences
• background subtraction
• Weber contrast analysis