Video Smoke Detection Algorithm Using Dark Channel Priori

摘要：

　　This paper proposes a dark channel priori based approach for early stage smoke detection in video sequence.Firstly,smoke exhibit less chrominance components and chromaticity analysis is employed to detect grayish pixels in video sequences.Secondly,the motion history image(MHI)method is proposed to capture the motion characteristics of smoke.This moving history representation can be used to determine the current movement of the smoke and to segment the motions induced by the smoke in a video scene.Finally,the intensity of the dark channel is a rough approximation of the thickness of the smoke.It can separate the smoke component from the background,and is used to validate the candidate smoke region.Experiments show that this method can achieve desired smoke region in various scenes with high smoke detection rate.

关键词： video smoke detection dark channel priori motion history image color model

作者: Miao Ligang Chen Yanjun Wang Aizhong

作者单位: College of Information Science and Engineering,Northeastern University,Shenyang 110819;R&D Departmen College of Information Science and Engineering,Northeastern University,Shenyang 110819 R&D Department,Gulf Security Technology Cooperation LTD,Qinhuangdao 066004

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 7405-7408

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）