@inproceedings{23e64547bbc04a538a50e1bbaaacdde0,
title = "Broken railway fastener detection based on adaboost algorithm",
abstract = "The detection of broken railway fastener is important to ensure the safety of the railway transport. This paper proposes an efficient method to detect and recognize the broken fastener with complex ballast railway images. Firstly, a from-coarse-to-fine strategy according to the sleeper region's gray and gradient characteristics is used to position the fastener, then the Haar-like feature set according to the fastener's geometrical characteristics is introduced. Finally, the fastener state is recognized by the AdaBoost-based algorithm. The method can detect fastener effectively and automatically with high positioning and recognizing accuracy and need not manual intervention. The experiment showed that the detection rate is satisfactory.",
keywords = "Adaboost, Cascade classifier, Haar-like, Railway fastener",
author = "Yiqi Xia and Fengying Xie and Zhiguo Jiang",
year = "2010",
doi = "10.1109/ICOIP.2010.303",
language = "英语",
isbn = "9780769542522",
series = "Proceedings - 2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010",
pages = "313--316",
booktitle = "Proceedings - 2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010",
note = "2010 International Conference on Optoelectronics and Image Processing, ICOIP 2010 ; Conference date: 11-11-2010 Through 12-11-2010",
}