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CLC number: TP39; U279.3

On-line Access: 2013-01-31

Received: 2012-07-16

Revision Accepted: 2012-12-20

Crosschecked: 2013-01-09

Cited: 4

Clicked: 2837

Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2013 Vol.14 No.2 P.98-106


Dust collector localization in trouble of moving freight car detection system

Author(s):  Fu-qiang Zhou, Rong Zou, He Gao

Affiliation(s):  School of Instrumentation Science and Optoelectronics Engineering, Beihang University, Beijing 100191, China

Corresponding email(s):   zfq@buaa.edu.cn

Key Words:  Hausdorff distance, Weighting function, Trouble detection, Rail transportation

Fu-qiang Zhou, Rong Zou, He Gao. Dust collector localization in trouble of moving freight car detection system[J]. Journal of Zhejiang University Science C, 2013, 14(2): 98-106.

@article{title="Dust collector localization in trouble of moving freight car detection system",
author="Fu-qiang Zhou, Rong Zou, He Gao",
journal="Journal of Zhejiang University Science C",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Dust collector localization in trouble of moving freight car detection system
%A Fu-qiang Zhou
%A Rong Zou
%A He Gao
%J Journal of Zhejiang University SCIENCE C
%V 14
%N 2
%P 98-106
%@ 1869-1951
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1200223

T1 - Dust collector localization in trouble of moving freight car detection system
A1 - Fu-qiang Zhou
A1 - Rong Zou
A1 - He Gao
J0 - Journal of Zhejiang University Science C
VL - 14
IS - 2
SP - 98
EP - 106
%@ 1869-1951
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1200223

For a long time, trouble detection and maintenance of freight cars have been completed manually by inspectors. To realize the transition from manual to computer-based detection and maintenance, we focus on dust collector localization under complex conditions in the trouble of moving freight car detection system. Using mid-level features which are also named flexible edge arrangement (FEA) features, we first build the edge-based 2D model of the dust collectors, and then match target objects by a weighted hausdorff distance method. The difference is that the constructed weighting function is generated by the FEA features other than specified subjectively, which can truly reflect the most basic property regions of the 3D object. Experimental results indicate that the proposed algorithm has better robustness to variable lighting, different viewing angle, and complex texture, and it shows a stronger adaptive performance. The localization correct rate of the target object is over 90%, which completely meets the need of practical applications.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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