关键词: Meanshift, 块运动, 烟雾, 时间窗

Abstract: Based on the analysis of partial microscopic moving characteristics of the internal smoke, a kind of smoke moving direction extracting algorithm is designed in this paper. The algorithm adopts Meanshift kernel function histogram to set up the model to describe the smoke moving characteristic and uses the Bhattachyarya coefficient to estimate the smoke block direction of the motion vector. In order to reduce the noise and the interference of rigid body, the algorithm counts moving data of each data block by the appropriate time window. This algorithm estimates the each smoke suspected area proportion in main movement and finally discriminates the smoke motion direction. The experimental results show that this algorithm performances well at extracting the smoke movement direction and reduces average searching point and improves searching precision, the features under a highly interference condition caused by thick black smoke and body moving, at the same time, it has a better ability to eliminate interference and provides a criterion for further smoke discrimination algorithm research.

Key words: Meanshift, block movement, smoke, time window