一种基于局部特征分块的目标跟踪算法

为了解决传统目标跟踪算法在天空背景下面临高能激光反射时图像像素灰度分布发生剧烈变化,从而导致目标遮挡或丢失的问题,采用一种基于局部特征分块思想的相关跟踪算法,根据局部特征对跟踪模板进行了分块处理,计算并选取其中特征稳定度高的块模板,在跟踪区域内对每个块做模板匹配,并进行了理论分析和试验验证.结果表明,该算法在强光干扰下能够有效地对目标实时稳定跟踪,且图像处理延迟时间在2ms以内.该研究对基于高能激光发射下的超高精度跟踪系统工作性能的保证是有帮助的.

A target tracking algorithm based on local feature segmentation

In order to solve the problem of occlusion or loss of targets caused by drastic change in gray distribution of image pixels by using traditional target tracking algorithms under high-energy laser reflection in the sky background, a correlation tracking algorithm based on local feature segmentation was adopted. The tracking template was divided into blocks according to local features. The block templates with high feature stability were calculated and selected. Template matching was performed for each block in the tracking area. The theoretical analysis and experimental verification were carried out. The results show that the algorithm can track the target stably in real time under strong light interference. And the image processing delay time is less than 2ms. This research is helpful to ensure the performance of ultra-high precision tracking system based on high-energy laser emission.