为解决传统摄影测量编码点定位依赖多种关系准则、判定复杂且识别不稳定的问题,提出一种采用基于改进YOLO v3的目标检测网络分割编码点、利用距离排序识别中心标记点的定位方法。首先针对编码标记点特点改进特征提取网络,从复杂背景中快速识别编码点,然后在预测框内进行图像处理,计算轮廓质心到中心的距离,通过距离排序定位中心圆形标记点,最后构建标尺编码点数据集用于网络训练和测试。实验结果表明,目标检测网络识别编码点的精度达到94.91%,受环境和噪声等的影响小,距离准则准确率高,该定位方法具有适应性好、鲁棒性高的优点。

In order to solve the problem that traditional photogrammetric coded point location depends on multiple relationship criteria, complex judgment, and unstable recognition, a localization method is proposed, which uses the target detection network based on improved YOLO v3 to segment the coding points, and uses distance sorting to identify the center mark points. First, the feature extraction network is improved according to the characteristics of the coded mark points, and the coded points are quickly identified from the complex background. Then, image processing is carried out in the prediction frame to calculate the distance from the centroid of the contour to the center, and then the circular mark points of the positioning center are sorted. Finally, the scale coding point data set is constructed for network training and testing. The experimental results show that the recognition accuracy of the target detection network for coded points reaches 94.91%, which is less affected by the environment and noise, and the distance criterion has high accuracy. The location method has the advantages of good adaptability and high robustness.