13th Asia Pacific Transportation Development Conference
Research on SFC Fast Bullet State Detection Method Combining Statistics and Conditional Random Field
Publication: Resilience and Sustainable Transportation Systems
ABSTRACT
It is difficult to accurately locate and extract a specific part or region in a fast elastic strip fastener system (SFC) with a single-layer base plate by using image processing technology. In this paper, a SFC fast strip state detection method based on the combination of statistics and conditional random field is proposed. Firstly, the target detection and extraction of the fast strip state of track fastener image on a specific feature scale are carried out by using statistical theory. Then, the fast strip region is segmented by conditional random field model and the strip region is extracted by using conditional random field model. Finally, the SFC fast spring is further detected by the precise location information of the fastener fast spring. The experimental results show that, the method of this paper can accurately extract and detect the SFC fast spring strip, and has better detection effect and accuracy in practical engineering applications.
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ACKNOWLEDGMENTS
The work was supported by National Natural Science Foundation of China (Grant No. 51975347). The work was also supported by Key Technology R&D Project of Shanghai Committee of Science and Technology (Grant No. 18030501300).
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Information & Authors
Information
Published In
Resilience and Sustainable Transportation Systems
Pages: 394 - 402
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Jun 29, 2020
Published in print: Jun 29, 2020
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