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Detection for Rail Surface Defects via Partitioned Edge Feature
IEEE Transactions on Intelligent Transportation Systems, 2022Visual inspection techniques for rail surface defects have become prevalent approaches to obtain information on rail surface damage. However, uneven illumination leads to illegibility of local information, and the change of the wheel-rail area results in the changeful background of the rail surface, both of which pose challenges to the visual ...
Xuefeng Ni +4 more
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A Visual Detection System for Rail Surface Defects
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2012Discrete surface defects are the most common anomalies of rails and they should be carefully inspected. However, it is a challenge to detect such defects in a vision system because of illumination inequality and the variation of reflection property of rail surfaces.
Qingyong Li, Shengwei Ren
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Morphological Detection and Extraction of Rail Surface Defects
IEEE Transactions on Instrumentation and Measurement, 2020Rail inspection by means of a visual system has been a subject of a number of publications in recent years. The main requirements with regard to such a system are that it has to be fast, nondestructive, and accurate. This article presents a system for rail defect detection and shape extraction utilizing morphological operations.
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A Coarse-to-Fine Model for Rail Surface Defect Detection
IEEE Transactions on Instrumentation and Measurement, 2019Computer vision systems have attracted much attention in recent years for use in detecting surface defects on rails; however, accurate and efficient recognition of possible defects remains challenging due to the variations shown by defects and also noise. This paper proposes a coarse-to-fine model (CTFM) to identify defects at different scales.
Haomin Yu +6 more
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Research on Rail Surface Defect Inspection System
Applied Mechanics and Materials, 2012In order to realize the inspection of rail surface defects with high speed and high precision, an automatic detection system based on machine vision is presented. The hardware structure of the system consists of the mechanical system, control system and visual imaging system.
Yu Hu, Jian Xu Mao, Jian Pin Mao
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Deep convolutional neural networks for detection of rail surface defects
2016 International Joint Conference on Neural Networks (IJCNN), 2016In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings. This huge amount of data makes it impossible to manually inspect the images and detect rail surface defects. Therefore, automated detection
Shahrzad Faghih-Roohi +4 more
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An Algorithm for the Detection and Measurement of Rail Surface Defects
Journal of the American Statistical Association, 1993Abstract Defects on the surface of railroad tracks have been the cause of growing concern over the past three decades. The automated detection and classification of rail surface defects would be of great assistance to rail maintenance planners, who develop grinding strategies to prevent the development of potentially dangerous deterioration. Videotaped
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Rail surface defect detection based on deep learning
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 2020In order to ensure the safety of rail transit, detecting the flaws on the rail surface is vitally important. Instead of present manual inspections, detecting defects on rail surface by an automatic approach enables the work more efficient and safe currently.
Xiaoqing Li, Ying Zhou, Hu Chen
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Heuristic Algorithms for Aggregating Rail‐Surface‐Defect Data
Journal of Transportation Engineering, 1994An optical inspection system has been developed to detect the presence of defects on the surface of rails. The system classifies each 6 in. (15 cm) length of railhead as defective or nondefective and generates large quantities of disaggregate, sequential condition data.
Roemer M. Alfelor, Sue McNeil
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Inspection of rail surface defects based on image processing
2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010), 2010A rail surface defects inspection method based on automated machine vision system is proposed in the paper. Two kinds of defect images including spalling of rail head and cracks in surface are analyzed with this method. Some related algorithms comprising denoising, image segmentation and feature extraction are applied in processing the images of rail ...
null Ze Liu +3 more
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