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基于LabVIEW的红外人体目标跟踪
引用本文:李孟儒,华宇宁,郝永平,张乐.基于LabVIEW的红外人体目标跟踪[J].成组技术与生产现代化,2014(2):46-49.
作者姓名:李孟儒  华宇宁  郝永平  张乐
作者单位:沈阳理工大学兵器科学技术研究中心,辽宁沈阳110159
基金项目:国家863计划资助项目(2009AA04Z167)
摘    要:针对红外图像序列信噪比低,缺少边缘及纹理信息,以及人体目标运动自主性强且姿态复杂多变的特点,选用Mean Shift目标跟踪算法,对红外人体目标进行跟踪.针对传统Mean Shift目标跟踪算法不能对尺度变化的红外目标进行有效跟踪的问题,对原有算法进行改进,使用边缘加权直方图与模板中心加权直方图计算Bhattacharyya系数的方式,实现核函数带宽的自适应,并利用界面友好的LabVIEW2011平台进行实现.通过两组实验证明了改进后算法的可行性和有效性.

关 键 词:红外图像  目标跟踪  Mean  Shift  LabVIEW

LabVIEW-based Target Tracking of Inf rared Body
LI Meng-ru,HUA Yu-ning,HAO Yong-ping,ZHANG Le.LabVIEW-based Target Tracking of Inf rared Body[J].Group Technology & Production Modernization,2014(2):46-49.
Authors:LI Meng-ru  HUA Yu-ning  HAO Yong-ping  ZHANG Le
Affiliation:(Weapons Science Technology Research Center, Shenyang Ligong University, Shenyang 110159, China)
Abstract:Aiming at low SNR infrared image sequences , the lack of edge and texture information ,as well as inde-pendent and the characteristics of strong human target mo-tion and gesture complex , the paper choosese Mean Shift tracking algorithm to track the target for infrared body .In-frared target can not scale effectively tracking changes in the traditional Mean Shift tracking algorithm ,this paper has im-proved the original Mean Shift algorithm and by using edge-weighted histograms and histogram templates center-weigh-ted way to calculate Bhattacharyya coefficient to achieve nu-clear adaptive function of bandwidth and use friendly inter-face LabVIEW2011 platform to achieve , and has finally proved the feasibility and effectiveness of the improved algo-rithm through two experiments .
Keywords:infrared image  target tracking  Mean Shift  LabVIEW
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