基于U-Net的列车轮对激光曲线提取

研究列车轮对条纹图像快速准确提取的方法,采用经典的U-Net网络模型,实现了激光条纹的精确分割,以构建模板的方式对分割后的图像采用灰度重心法达到亚像素的提取。首先利用U-Net网络模型对激光条纹进行分割,然后用模板法初步找到光条中心,最后再使用灰度重心法实现快速、准确的激光曲线提取。结果表明,该方法可以有效地克服动态环境下背景噪声以及亮斑对激光条纹提取带来的影响。

Laser curve extraction of train wheelset based on U-Net

The method for rapid and accurate extraction of fringe images of wheel pairs is studied.The classic UNet network model is used to achieve precise segmentation of laser stripes,and the gray center of gravity method is used to achieve sub-pixel extraction of the segmented image in the form of a template.Firstly,the U-net network model is used to do laser stripe segmentation,then the template method is used to find the center of the light bar,and finally the gray center of gravity method is used to achieve fast and accurate laser curve extraction.Experimental results show that this method can effectively overcome the effects of background noise and bright spots on laser stripe extraction under dynamic environment.