Dust collector localization in trouble of moving freight car detection system

Fu-qiang ZHOU; Rong ZOU; He GAO

doi:10.1631/jzus.C1200223

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Dust collector localization in trouble of moving freight car detection system

计算机工程 | Updated：2022-12-09

- Dust collector localization in trouble of moving freight car detection system
- Dust collector localization in trouble of moving freight car detection system
- 信息与电子工程前沿（英文） 2013年14卷第2期页码：98-106
- Affiliations：
  
  School of Instrumentation Science and Optoelectronics Engineering, Beihang University, Beijing 100191, China
- Author bio：
  
  [ "Fu-qiang ZHOU, zfq@buaa.edu.cn" ]
- Funds：
  
  Project supported by the National Natural Science Foundation of China (No. 61072134) and the Research Fund for the Doctoral Program of Higher Education of China (No. 20101102110033)
- DOI：10.1631/jzus.C1200223
  中图分类号： TP39;U279.3
- 收稿：2012-07-16，
  
  修回：2013-;9-;1，
  
  纸质出版：2013-02
- Accepted：
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Dust collector localization in trouble of moving freight car detection system[J]. 信息与电子工程前沿（英文）, 2013,14(2):98-106.

Fu-qiang ZHOU, Rong ZOU, He GAO. Dust collector localization in trouble of moving freight car detection system[J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(2): 98-106.
Dust collector localization in trouble of moving freight car detection system[J]. 信息与电子工程前沿（英文）, 2013,14(2):98-106. DOI： 10.1631/jzus.C1200223.

Fu-qiang ZHOU, Rong ZOU, He GAO. Dust collector localization in trouble of moving freight car detection system[J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(2): 98-106. DOI： 10.1631/jzus.C1200223.

摘要

Abstract

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.

关键词

Keywords

references

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