改进的Mean Shift算法在前视声呐运动目标跟踪中的应用

Application of improved mean shift algorithm in moving target tracking of forward-looking sonar

多波束前视声呐具有成像速度快、分辨率高的优点,是进行水下目标探测、跟踪和监控的重要设备。针对多波束前视声呐运动目标的跟踪问题,提出了一种改进的MeanShift算法。该算法利用经典的MeanShift算法实现目标的帧间定位,通过基于图像序列的背景消减法实现运动目标分割,根据分割后目标的位置和大小对Mean Shift跟踪框进行更新,并重新建立跟踪模型来迭代实现目标的准确定位和跟踪。实验结果表明,改进后的算法可实现目标跟踪框随目标大小和形状的更新,对目标的定位更加准确。因此,该算法具有应用于水下目标精确跟踪和定位的潜力。

The multi-beam forward-looking sonar has the advantages of high imaging speed and high resolution.It is an important device for underwater target detection,tracking and monitoring.Aiming at the tracking problem of multi-beam forward-looking sonar,an improved Mean Shift algorithm is proposed.In the algorithm,the classical Mean Shift algorithm is used to locate the inter-frame of the target,and the background subtraction method based on the image sequence is used to segment the moving target.The Mean Shift tracking box is updated according to the position and size of the segmented target,and the tracking model is re-established to achieve accurate localization and tracking of the target through iteration.The experimental results show that the improved algorithm can update the target tracking frame with the size and shape of the target,and the target localization is more accurate.Therefore,the algorithm has the potential to be applied to accurate tracking and localization of underwater targets.