Accurate and rapid contour extraction of visual measurement for rail wear

Wen-tao LI; Pei-jun WANG; Xiao-min TANG

doi:10.3788/OPE.20182601.0238

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Accurate and rapid contour extraction of visual measurement for rail wear

更新时间：2020-08-13

- Accurate and rapid contour extraction of visual measurement for rail wear
- Optics and Precision Engineering Vol. 26, Issue 1, Pages: 238-244(2018)
- 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：
- 基金信息：
- DOI：10.3788/OPE.20182601.0238
  CLC： U213.42
- Received：08 May 2017，
  
  Accepted：18 July 2017，
  
  Published：25 January 2018
- 稿件说明：
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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：

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.

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Keywords

references

占栋, 于龙, 肖建, 等.钢轨轮廓全断面高精度动态视觉测量方法研究[J].铁道学报, 2015, 37(9):96-106.

ZHAN D, YU L, XIAO J, et al .. Study on high-accuracy vision measurement approach for dynamic inspection of full cross-sectional rail profile[J]. Journal of the China Railway Society , 2015, 37(9):96-106. (in Chinese)

康高强, 李春茂, 秦莉娟, 等.一种钢轨动态轮廓数据校准方法研究[J].传感技术学报, 2015, 28(2):221-226.

KANG G Q, LI CH M, QIN L J, et al .. Research on a method of calibrating dynamic rail profile data[J]. Chinese Journal of Sensors and Actuators , 2015, 28(2):221-226. (in Chinese)

华长权, 寇东华, 付石林, 等.几种钢轨磨损检测方法和仪器的对比分析[J].中国铁路, 2013(4):67-70.

HUA CH Q, KOU D H, FU SH L, et al .. Approach comparison of several rail wear instrumentation and measurements[J]. Chinese Railways , 2013(4):67-70. (in Chinese)

WANG X H, WAN Y, LI R, et al .. A multi-object image segmentation C-V model based on region division and gradient guide[J]. Journal of Visual Communication and Image Representation , 2016, 39:100-106.

陈恺, 陈芳, 戴敏, 等.基于萤火虫算法的二维熵多阈值快速图像分割[J].光学精密工程, 2014, 22(2):517-523.

CHEN K, CHEN F, DAI M, et al .. Fast image segmentation with multilevel threshold of two-dimensional entropy based on firefly algorithm[J]. Opt. Precision Eng ., 2014, 22(2):517-523. (in Chinese)

HARUKI T, KIKUCHI K. Video camera system using fuzzy logic[J]. IEEE Transactions on Consumer Electronics , 1992, 38(3):624-634.

杨海涛, 常义林, 王静, 等.一种基于亮度直方图的自动曝光控制方法[J].光学学报, 2007, 27(5):841-847.

YANG H T, CHANG Y L, WANG J, et al .. A new automatic exposure algorithm for video cameras using luminance histogram[J]. Acta Optica Sinica , 2007, 27(5):841-847. (in Chinese)

李凤娇, 李小菁, 刘震.基于多尺度分析的激光光条中心点坐标提取方法[J].光学学报, 2014, 34(11):1110002.

LI F J, LI X J, LIU ZH. A multi-scale analysis based method for extracting coordinates of laser light stripe centers[J]. Acta Optica Sinica , 2014, 34(11):1110002. (in Chinese)

STEGER C. An unbiased detector of curvilinear structures[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence , 1998, 20(2):113-125.

孙军华, 王恒, 刘震, 等.钢轨磨耗动态测量中激光光条中心的快速提取[J].光学精密工程, 2011, 19(3):690-696.

SUN J H, WANG H, LIU ZH, et al .. Rapid extraction algorithm of laser stripe center in rail wear dynamic measurement[J]. Opt. Precision Eng ., 2011, 19(3):690-696. (in Chinese)

贾倩倩, 王伯雄, 罗秀芝.光切法形貌测量中光条中心的亚像素提取[J].光学精密工程, 2010, 18(2):390-396.

JIA Q Q, WANG B X, LUO X ZH. Extraction of central positions of light stripe in sub-pixel in 3D surface measurement based on light sectioning method[J]. Opt. Precision Eng ., 2010, 18(2):390-396. (in Chinese)

中华人民共和国铁道部.高速铁路有砟轨道线路维修规则(试行)[M].北京:中国铁道出版社, 2013.

People's Republic of China Ministry of Railways. Maintenance Rules for Ballasted Track High-speed Railway Track ( Trial )[M]. Beijing:China Railway Publishing House, 2013. (in Chinese)

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