Mean-shift跟踪算法及其在光电跟踪系统中的应用

Mean-shift tracking algorithm and its application in optoelectronic tracking system

针对光电跟踪系统中实时提取运动目标脱靶量的应用需求,设计了一种基于灰度直方图的Mean-shift图像跟踪算法,对算法中目标模型与候选模型的建立进行了改进,抑制了背景像素对目标跟踪产生的影响。算法在系统上位机Visual C++6.0平台上实现,当光电跟踪系统捕获到运动目标后,利用Mean-shift图像跟踪算法跟踪运动目标,并实时将运动目标脱靶量作为伺服控制系统的输入信号,驱动跟踪器跟踪目标。实验结果表明:设计的算法可以实时、准确、有效地跟踪运动目标,使稳定后的脱靶量换算得到的角偏差量控制在30″之内。

In order to fulfill the requirement to extract miss distance of moving target in real time in optoelec- tronic tracking system, a Mean-shift image tracking algorithm based on gray histogram is designed. The target model and the candidate model of the algorithm are improved, and the impact of background pixels on target tracking is suppressed. The algorithm is implemented in the Visual C ＋ ＋ 6.0 platform in the upper computer of the system. When the optoelectronic tracking system captures the moving target, the system uses the Mean- shift image tracking algorithm to track the moving target. The miss distance is used as the input signal of the servo control system to drive the tracking device to track the target. Experiment results show that the proposed Mean-shift algorithm is able to track the moving target in real time precisely and effectively so that the angle deviation can be limited within 30 arc sec.