Rail defect detection with real time image processing technique

Canan Tastimur, Mehmet Karaköse, E. Akin, I. Aydin
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引用次数: 24

Abstract

Rail defect detection has a great importance for railway transportation. Because faults on the rails cause to problems such as the cost, the disruption of transportation and the safety. In this study, based real-time video processing algorithm used Morphological feature extraction is recommended to detection defects on railroad. The rail is detected by applying Hough Transform and image processing techniques to rail images obtained from the real time camera. Features of the detected rail images are extracted with applying morphological operations and defected regions are identified. Headcheck, fracture, scour and undulation failures are detected through proposed method. In this study, results with low uptime and high success rate are acquired by performing all steps of proposed algorithm to the images of rail taken under different lighting and direction.
基于实时图像处理技术的钢轨缺陷检测
钢轨缺陷检测对铁路运输具有重要意义。因为轨道上的故障会造成成本、运输中断和安全等问题。本研究提出了一种基于形态学特征提取的实时视频处理算法,用于铁路缺陷检测。利用霍夫变换和图像处理技术对实时摄像机采集的轨道图像进行检测。利用形态学运算提取检测到的轨道图像的特征,识别缺陷区域。通过该方法可检测出头检、断裂、冲刷和波动等故障。在本研究中,通过对不同光照和方向下拍摄的轨道图像执行所提出算法的所有步骤,获得了正常运行时间短、成功率高的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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