深空背景下基于Delaunay三角剖分的多成像器目标对应算法

Algorithm Based on Delaunay Triangulation for Target Correspondence across Multiple Cameras in Deep Space

针对深空背景下,目标距离成像器较远,目标在多个成像器平面呈弱小目标,目标点之间的形状及灰度特征没有明显区别的现状,提出了基于目标点之间形成的几何组合来完成目标点在不同成像平面对应的算法。该算法首先对各个成像器目标检测后获取的目标点集根据成像器间的姿态信息进行旋转补偿,然后对补偿后的目标点集进行Delaunay三角剖分,最后根据剖分后三角形的相似性测度来完成多个成像器平面的目标对应。对算法在各个场景下的目标对应性能进行了仿真与分析。

In the deep space,targets are far away from the cameras and become dim targets with less shape and gray features in the image planes.It is an essential problem of target correspondence across multiple cameras.A novel algorithm based on geometries consisting of detected targets in multiple cameras was proposed.The algorithm firstly compensated the rotation effect of the detected targets set.Then,Delaunay triangulation was used to divide set of compensated points.Finally,triangle similarity was employed for target correspondence.According to simulation and analysis,the algorithm dealt with target correspondence across multiple cameras in deep space effectively.