Track Surface Defect Detection Based on Image Processing

机译：基于图像处理的轨道表面缺陷检测

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摘要

In this paper, computer vision-based methods are presented to detect the rail track surface defects automatically. The detection is the key foundation to inspect and assess railways, and for the operation safety and rail maintenance, railways inspection is the critical task. To achieve this goal, the rail surface edge's likelihood is investigated, and the Canny edge detector for defects extraction is introduced to guarantee the detection of the rail surface damage accurately. The analysis performed on some image data captured on the field has demonstrated encouraging detection performance on rail track surface defect detection.

机译：本文提出了一种基于计算机视觉的方法来自动检测轨道表面缺陷。检测是铁路检查和评估的关键基础，对于运行安全和铁路维护而言，铁路检查是关键任务。为了达到这个目的，研究了轨道表面边缘的可能性，并引入了用于缺陷提取的Canny边缘检测器，以确保准确地检测出轨道表面损伤。对在现场捕获的一些图像数据进行的分析表明，在轨道表面缺陷检测方面的检测性能令人鼓舞。

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来源
《Proceedings of the 3rd international conference on electrical and information technologies for rail transportation: transportation》|2017年|225-232|共8页
会议地点
作者
Yuxin Liu; Xiukun Wei;
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作者单位

State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China;

State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Image processing; Defect detection; Track surface; Field image analysis;

机译：图像处理;缺陷检测；履带表面；现场图像分析;

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4. Track Surface Defect Detection Based on Image Processing [C] . Yuxin Liu, Xiukun Wei International conference on electrical and information technologies for rail transportation: transportation . 2018

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Track Surface Defect Detection Based on Image Processing

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