Automatic Fastener Classification and Defect Detection in Vision-Based Railway Inspection Systems

@article{Feng2014AutomaticFC,
  title={Automatic Fastener Classification and Defect Detection in Vision-Based Railway Inspection Systems},
  author={Hao Feng and Zhiguo Jiang and Fengying Xie and Ping Yang and Jun Shi and Long Chen},
  journal={IEEE Transactions on Instrumentation and Measurement},
  year={2014},
  volume={63},
  pages={877-888}
}
The detection of fastener defects is an important task in railway inspection systems, and it is frequently performed to ensure the safety of train traffic. Traditional inspection is usually operated by trained workers who walk along railway lines to search for potential risks. However, the manual inspection is very slow, costly, and dangerous. This paper proposes an automatic visual inspection system for detecting partially worn and completely missing fasteners using probabilistic topic model… CONTINUE READING
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