钢轨磨损视觉测量的轮廓精确快速提取

李文涛; 王培俊; 唐晓敏

doi:10.3788/OPE.20182601.0238

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钢轨磨损视觉测量的轮廓精确快速提取

信息科学 | 更新时间：2020-08-13

- 钢轨磨损视觉测量的轮廓精确快速提取
- Accurate and rapid contour extraction of visual measurement for rail wear
- 光学精密工程 2018年26卷第1期页码：238-244
- 作者机构：
  
  西南交通大学机械工程学院, 四川成都 610031
- 作者简介：
  
  [ "李文涛(1991-), 男, 湖北仙桃人, 博士研究生, 2013年于西南交通大学获得学士学位, 主要从事视觉测量与数字化图像处理方面的研究。E-mail:jxsjtao@my.swjtu.edu.cn" ]
  [ "王培俊(1962-), 女, 浙江宁波人, 教授, 1983年于西南交通大学获得学士学位, 1987年于哈尔滨工业大学获得硕士学位, 2004年于西南交通大学获得博士学位。2002~2003年瑞典LUND大学访问学者。主要从事数字化设计与检测、虚拟设计、VR技术等研究。E-mail:pjwang123@swjtu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金青年科学基金资助项目(51305368);四川省科技支撑计划资助项目(2013GZX0154)
- DOI：10.3788/OPE.20182601.0238
  中图分类号： U213.42
- 收稿日期：2017-05-08，
  
  录用日期：2017-7-18，
  
  纸质出版日期：2018-01-25
- 稿件说明：
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李文涛, 王培俊, 唐晓敏. 钢轨磨损视觉测量的轮廓精确快速提取[J]. 光学精密工程, 2018,26(1):238-244.

Wen-tao LI, Pei-jun WANG, Xiao-min TANG. Accurate and rapid contour extraction of visual measurement for rail wear[J]. Optics and precision engineering, 2018, 26(1): 238-244.
李文涛, 王培俊, 唐晓敏. 钢轨磨损视觉测量的轮廓精确快速提取[J]. 光学精密工程, 2018,26(1):238-244. DOI： 10.3788/OPE.20182601.0238.

Wen-tao LI, Pei-jun WANG, Xiao-min TANG. Accurate and rapid contour extraction of visual measurement for rail wear[J]. Optics and precision engineering, 2018, 26(1): 238-244. DOI： 10.3788/OPE.20182601.0238.

摘要

为保证钢轨磨损动态视觉测量的高精度，综合图像获取和图像处理技术，实现了清晰光条图像获取和光条中心点亚像素坐标精确提取。根据光条与背景环境亮度的高对比度，提出一种依据光条亮度的相机自动曝光法，用于获取清晰的光条图像；分析图像光条法线方向的亮度衰变特征，采用动态阈值分割法初步提取光条，滤除图像背景的同时保留光条法线方向的亮度衰减信息；根据图像过度曝光信息确定光条中心点像素大致位置，再对分割的光条图像相对应像素位置点计算Hessian矩阵，获取光条中心点的亚像素坐标。采用MFC编写应用程序进行试验，在不同光照环境和背景物的干扰下，该方法可精确地提取光条中心，与经典Steger算法相比提取精度偏差为0.05 pixel，运算时间节约40%。试验结果验证了该方法稳定性好，有较强的抗干扰能力，较好地满足钢轨磨损测量的现场要求。

Abstract

In order to ensure the high precision of dynamic visual measurement of rail abrasion

image acquisition and image processing technology were used to get clear light-stripe image and extract the sub-pixel coordinates of the light-stripe accurately. First

according to the high contrast between the light-stripe and the background brightness

a method of automatic exposure of the camera based on the brightness of the light-stripe was proposed

which could ensure a clear image of the light-stripe. Then the dynamic threshold segmentation method was presented to extract the light-stripe preliminarily according to the lightness decay feature of the light-stripe in the normal direction

this method can filter out the background of the image while preserving the normal attenuation of light. Finally

according to the overexposure information of the image to determine the approximate position of the center point of the light-stripe

then the Hessian matrix was calculated for the corresponding pixel position of the segmented image to obtain the sub-pixel coordinates of the light-stripe. Using MFC to write application for testing

under different illumination and background interference

this method can accurately extract the center of light-stripe

the extraction accuracy is 0.05 pixel and the computation time is reduced by 40% compared with the classical Steger algorithm. Experimental results show that the proposed method has good stability and strong anti-interference ability

can meet the requirements of the rail abrasion measurement.

关键词

Keywords

references

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