关键词: Harris, 特征点, Lucas-Kanade目标跟踪, 烟雾特征, 烟雾识别

Abstract: Aiming at the problem of lower real time, higher false alarm rate and miss rate in the existing video fire smoke detection methods, the feature that early smoke movement is slow, main movement trend is upward and pixel intensity change is consistent in successive frames is found after depth analysis of smoke  image characteristics. Multiple feature smoke detection is realized through the Harris detection algorithm to find intensity changes and image edge feature point, based on the optical flow and the motion field correspondence by imaging plane optical flow estimation smoke changes in relative motion, calculation of motion vector information. This algorithm based on the smoke intensity change feature point as detection object greatly reduces the amount of data and shortens processing time. Because the smoke local and global characteristics are studied and applied, the proposed algorithm has the strong robustness and high detection accuracy rate.

Key words: Harris, feature point, Lucas-Kanade target tracking, smoke features, smoke recognition