基于主动轮廓模型的交通场景运动目标提取算法

在交通监控中,从复杂的交通场景中精确地分割出运动目标是至关重要的。目前,经典的运动目标检测算法有背景差法和帧差法。当场景中存在阴影时,这两种方法都不能够精确地提取运动目标。提出了一种基于主动轮廓模型的运动目标提取算法。通过阴影检测,从运动目标中获得消除阴影的初始轮廓,然后通过主动轮廓模型逼近运动目标真实轮廓。实验表明,该算法既可以消除阴影和噪声的影响,又可以保持运动目标完整。

Traffic Motion Object Extrication Algorithm Based on Active Contour Model

In intelligent transport system,it is very important to precisely segment motion object from complex scene.Background difference and frame difference are two classic motion object extraction algorithms.If there are shadows associated to moving objects,both of the methods can＇t extract moving object precisely.With this problem,this paper proposes a motion object extraction algorithm based on active contour model.The following steps are performed in the proposed algorithm.Firstly,moving areas involving shadows are segmented with classical background difference algorithm.Secondly,perform shadow detection and coarsely removal,then using grid method to extract initial contours.Finally,use active contour model approach to the contour of the real object by iteratively tuning the parameter of the model.Experiments show the algorithm can remove the shadow and keep the integrity of moving object.