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图学学报

图学学报 ›› 2022, Vol. 43 ›› Issue (2): 324-332.DOI: 10.11996/JG.j.2095-302X.2022020324

• 计算机图形学与虚拟现实 • 上一篇    下一篇

基于道钉中心点定位的几何特征扣件定位算法

  

  1. 华东交通大学软件学院，江西 南昌 330013
  • 出版日期:2022-04-30 发布日期:2022-05-07
  • 基金资助:

    国家自然科学基金项目(61663009)；

    江西省科技支撑计划重点项目(20161BBE50081)

Track fastener localization algorithm based on geometric features and the spike center point localization

  1. School of Software, East China Jiaotong University, Nanchang Jiangxi 330013, China
  • Online:2022-04-30 Published:2022-05-07
  • Supported by:

    National Natural Science Foundation of China (61663009); 

    Key Project Supported by the Technology Support Program of Jiangxi Province of China (20161BBE50081)

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摘要： 针对因轨道图像中图像歪斜、尺寸不一等导致定位失效、精度降低的问题，提出基于道钉中心点
定位的几何结构特征扣件定位算法。采用先定位道钉中心点再定位扣件的思想。首先在图像预处理得到边缘图像
的基础上，对图像边缘进行腐蚀与膨胀处理，使道钉边缘具备似圆性，再通过改进 Hough 变换进行圆形检测定位
道钉所处大致区域并进行扩充，然后从原图像中粗提取出道钉区域图像；随后进行边缘检测并采用 OpenCV 轮廓
提取及多边形检测算法精确拟合道钉六边形，计算出道钉中心点；最后根据提出的几何结构特征扣件定位算法计
算各顶点的位置，从而实现轨道扣件的精确定位。仿真实验结果表明，该算法定位准确度达 99.33%，定位精度
达 0.997，定位速率为 29.8 张/秒，优于相关对比算法。同时，在不同的天气条件、道钉腐蚀、道钉遮挡等情况下，
新算法具备较好的鲁棒性及一定的抗干扰能力。

关键词: 扣件定位, 道钉定位, 轮廓提取, 多边形检测, 几何特征

Abstract: To solve the problems of positioning failure and accuracy reduction caused by skewedness and nonstandard
size of images in the track image, a fastener positioning algorithm based on the spike center point location and
geometric structure features was proposed. The new method adopted the idea of first locating the center point of the
spike, and then locating the fasteners with geometric features. Based on the edge image obtained by image
preprocessing, the edges of track spike in the image would be characteristic of roundness after being corroded and
dilated. Then, by means of the Hough transform circle detection algorithm, the rough area of the spike was located and
expanded, so that the spike area could be roughly extracted from the original image. The edges of spike area image
were then detected and OpenCV, a contour extraction and polygon detection algorithm, was employed to accurately fit
the spike hexagon and calculate the spike center point. Finally, the coordinates of each vertex of the fastener bounding
box was obtained using the fastener location algorithm proposed based on geometric structure features. The
experiment results show that the positioning accuracy of the new algorithm is 99.33%, the precision is 0.997, and the
speed is 29.8 fps, superior to the algorithms compared. Meanwhile, under different circumstances, such as weather
conditions, spike corrosion, or occlusion, the new algorithm displays better robustness and anti-interference ability.

Key words: fastener positioning, spike positioning, contour extraction, polygon detection, geometric features

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