Dust collector localization in trouble of moving freight car detection system

Fu-qiang ZHOU; Rong ZOU; He GAO

doi:10.1631/jzus.C1200223

Your Location：

Home >

Browse articles >

Dust collector localization in trouble of moving freight car detection system

Computer Engineering | 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
- Frontiers of Information Technology & Electronic Engineering Vol. 14, Issue 2, Pages: 98-106(2013)
- Affiliations：
  
  School of Instrumentation Science and Optoelectronics Engineering, Beihang University, Beijing 100191, China
- Author bio：
  
  [ "Fu-qiang ZHOU, zfq@buaa.edu.cn" ]
- Funds：
- DOI：10.1631/jzus.C1200223
  CLC： TP39;U279.3
- Received：16 July 2012，
  
  Revised：2013-;9-;1，
  
  Published：2013-02
- Accepted：
Scan QR Code
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：

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

Y. Amit . . A nonlinear variational problem for image matching . . SIAM J. Sci. Comput. , , 1994 . . 15 ( ( 1 ): ): 207 - - 224 . . DOI: 10.1137/0915014 http://doi.org/10.1137/0915014 . .

Y. Amit . . Sparse Models: Formulation, Training, and Statistical Properties . . The MIT Press, Cambridge, US , , 2002 . . p.121 - - 137 . . . .

Y. Amit , , , U. Grenander , , , M. Piccioni . . Structural image restoration through deformable templates . . J. Am. Stat. Assoc. , , 1991 . . 86 ( ( 414 ): ): 376 - - 387 . . DOI: 10.1080/01621459.1991.10475053 http://doi.org/10.1080/01621459.1991.10475053 . .

R. Bajcsy , , , S. Kovacic . . Multiresolution elastic matching . . Comput. Vis. Graph. Image Process. , , 1989 . . 46 1 - - 21 . . DOI: 10.1016/S0734-189X(89)80014-3 http://doi.org/10.1016/S0734-189X(89)80014-3 . .

C. Chesnaud , , , P. Réfrégier , , , V. Boulet . . Statistical region snake-based segmentation adapted to different physical noise models . . IEEE Trans. Pattern Anal. Mach. Intell. , , 1999 . . 21 ( ( 11 ): ): 1145 - - 1157 . . DOI: 10.1109/34.809108 http://doi.org/10.1109/34.809108 . .

H. Chui , , , A. Rangarajan . . A New Algorithm for Non-rigid Point Matching . . IEEE Conf. on Computer Vision and Pattern Recognition , , 2000 . . p.44 - - 51 . . DOI: 10.1109/CVPR.2000.854733 http://doi.org/10.1109/CVPR.2000.854733 . .

P. de Ruvo , , , A. Distante , , , E. Stella , , , F. Marino . . A GPU-Based Vision System for Real Time Detection of Fastening Elements in Railway Inspection . . IEEE Int. Conf. on Image Processing , , 2009 . . p.2333 - - 2336 . . DOI: 10.1109/ICIP.2009.5414438 http://doi.org/10.1109/ICIP.2009.5414438 . .

M.P. Dubuisson , , , A.K. Jain . . A Modified Hausdorff Distance for Object Matching . . Proc. 12th Int. Conf. on Pattern Recognition , , 1994 . . p.566 - - 568 . . DOI: 10.1109/ICPR.1994.576361 http://doi.org/10.1109/ICPR.1994.576361 . .

U. Grenander . . A unified approach to pattern analysis . . Adv. Comput. , , 1970 . . 10 ( ( 1 ): ): 175 - - 216 . . DOI: 10.1016/S0065-2458(08)60436-2 http://doi.org/10.1016/S0065-2458(08)60436-2 . .

J.M. Hart , , , E. Resendiz , , , B. Freid , , , S. Sawadisavi , , , C. Barkan , , , N. Ahuja . . Machine Vision Using Multi-spectral Imaging for Undercarriage Inspection of Railroad Equipment . . Proc. 8th World Congress on Railway Research , , 2008 . . p.1 - - 8 . . . .

R.I. Hartley , , , F. Kahl . . Global optimization through rotation space search . . Int. J. Comput. Vis , , 2009 . . 82 ( ( 1 ): ): 64 - - 79 . . DOI: 10.1007/s11263-008-0186-9 http://doi.org/10.1007/s11263-008-0186-9 . .

O. Jesorsky , , , K. Kirchberg , , , R.W. Frischholz . . Robust face detection using the Hausdorff distance . . LNCS , , 2001 . . 2091 90 - - 95 . . DOI: 10.1007/3-540-45344-x_14 http://doi.org/10.1007/3-540-45344-x_14 . .

M. Kass , , , A. Witkin , , , D. Terzopoulos . . Snakes: active contour models . . Int. J. Comput. Vis , , 1988 . . 1 ( ( 4 ): ): 321 - - 331 . . DOI: 10.1007/BF00133570 http://doi.org/10.1007/BF00133570 . .

H. Li , , , R. Hartley . . The 3D-3D Registration Problem Revisited. IEEE 11th Int. Conf . . on Computer Vision , , 2007 . . p.1 - - 8 . . DOI: 10.1109/ICCV.2007.4409077 http://doi.org/10.1109/ICCV.2007.4409077 . .

K.H. Lin , , , K.M. Lam , , , W.C. Siu . . Spatially eigen- weighted Hausdorff distances for human face recognition . . Pattern Recogn. , , 2003 . . 36 ( ( 8 ): ): 1827 - - 1834 . . DOI: 10.1016/S0031-3203(03)00011-6 http://doi.org/10.1016/S0031-3203(03)00011-6 . .

R. Liu , , , Y. Wang . . Principle and Application of TFDS , , : : Beijing China Railway Publication , , 2005 . . p.1 - - 20 . . . .

F. Marino , , , A. Distante , , , P.L. Mazzeo , , , E. Stella . . A real-time visual inspection system for railway maintenance: automatic hexagonal-headed bolts detection . . IEEE Trans. Syst. Man. Cybern. Part C Appl. Rev. , , 2007 . . 37 ( ( 3 ): ): 418 - - 428 . . DOI: 10.1109/TSMCC.2007.893278 http://doi.org/10.1109/TSMCC.2007.893278 . .

D. Metaxas , , , E. Koh , , , N.I. Badler . . Multi-level shape representation using global deformations and locally adaptive finite elements . . Int. J. Comput. Vis. , , 1997 . . 25 ( ( 1 ): ): 49 - - 61 . . DOI: 10.1023/A1007929702347 http://doi.org/10.1023/A1007929702347 . .

C. Olsson , , , F. Kahl , , , M. Oskarsson . . Branch-and-bound methods for Euclidean registration problems . . IEEE Trans. Pattern Anal. Mach. Intell. , , 2009 . . 31 ( ( 5 ): ): 783 - - 794 . . DOI: 10.1109/TPAMI.2008.131 http://doi.org/10.1109/TPAMI.2008.131 . .

M. Riesenhuber , , , T. Poggio . . Models of object recognition . . Nat. Neurosci. , , 2000 . . 3 1199 - - 1204 . . DOI: 10.1038/81479 http://doi.org/10.1038/81479 . .

W.J. Rucklidge . . Efficiently locating objects using the Hausdorff distance . . Int. J. Comput. Vis. , , 1997 . . 24 ( ( 3 ): ): 251 - - 270 . . DOI: 10.1023/A:1007975324482 http://doi.org/10.1023/A:1007975324482 . .

F. Shi , , , J. Yang , , , Y. Zhu . . Automatic segmentation of bladder in CT images . . J. Zhejiang Univ.-Sci. A , , 2009 . . 10 ( ( 2 ): ): 239 - - 246 . . DOI: 10.1631/jzus.A0820157 http://doi.org/10.1631/jzus.A0820157 . .

H. Suk , , , S. Lee . . A novel Bayesian framework for discriminative feature extraction in brain-computer interfaces . . IEEE Trans. Pattern Anal. Mach. Intell. , , 2013 . . 35 ( ( 2 ): ): 286 - - 299 . . DOI: 10.1109/TPAMI.2012.69 http://doi.org/10.1109/TPAMI.2012.69 . .

R. Szeliski , , , S. Lavallée . . Matching 3-D anatomical surfaces with non-rigid deformations using octree-splines . . Int. J. Comput. Vis. , , 1996 . . 18 ( ( 2 ): ): 171 - - 186 . . DOI: 10.1007/BF00055001 http://doi.org/10.1007/BF00055001 . .

H. Tan , , , Y.J. Zhang . . A novel weighted Hausdorff distance for face localization . . Image Vis. Comput. , , 2006 . . 24 ( ( 7 ): ): 656 - - 662 . . DOI: 10.1016/j.imavis.2005.05.011 http://doi.org/10.1016/j.imavis.2005.05.011 . .

S. Yella , , , M. Dougherty , , , N.K. Gupta . . Condition monitoring of wooden railway sleepers . . Transp. Res. Part C Emerg. Technol. , , 2009 . . 17 ( ( 1 ): ): 38 - - 55 . . DOI: 10.1016/j.trc.2008.06.002 http://doi.org/10.1016/j.trc.2008.06.002 . .

H. Zhang , , , J. Yang , , , W. Tao , , , H. Zhao . . Vision method of inspecting missing fastening components in high-speed railway . . Appl. Opt. , , 2011 . . 50 ( ( 20 ): ): 3658 - - 3665 . . DOI: 10.1364/AO.50.003658 http://doi.org/10.1364/AO.50.003658 . .

S.C. Zhu , , , A. Yuille . . Region competition: unifying snakes, region growing, and Bayes/MDL for multiband image segmentation . . IEEE Trans. Pattern Anal. Mach. Intell. , , 1996 . . 18 ( ( 9 ): ): 884 - - 900 . . DOI: 10.1109/34.537343 http://doi.org/10.1109/34.537343 . .

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

No data

Related Author

No data

Related Institution

No data

Chat

Address：Zhejiang University Press, 148 Tianmushan Road, Hangzhou, China Postal code：310028
Tel：+86-571-88273162 Email：fitee@zju.edu.cn
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰