@inproceedings{0d1b5e9331574330b7c7e62e49f261e5,
title = "Train wheel edge detection and image object region segmentation",
abstract = "Machine vision based mechanical appearance fault analysis and inspection is getting broad applications in past decades. Train wheel tread damage is a common fault pattern. The precedent step of the routine vision based analysis work is to get an image that includes the wheel surface. In this paper, a wheel curve edge extraction and object region segmentation framework is proposed. Firstly the salient rail line edge is extracted for a previous segmentation step and a sub image is acquired. Then line segment detector is used to detect the lines along the contours. And the wheel and shadow curve edge are approximated by line segments sets. Through certain geometry rules, the two edge lines are extracted. Finally the wheel object region is extracted perfectly and accurately.",
keywords = "Object region segmentation, Rail line extraction, Train wheel edge detection, Visual inspection system",
author = "Guo Nan and Shengfang Lu and Junen Yao",
note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; International Symposium on Infrared Technology and Application and the International Symposiums on Robot Sensing and Advanced Control ; Conference date: 09-05-2016 Through 11-05-2016",
year = "2016",
doi = "10.1117/12.2246739",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Haimei Gong and Aiguo Song",
booktitle = "Infrared Technology and Applications, and Robot Sensing and Advanced Control",
address = "美国",
}