Low-Cost Fastener Inspection System on High-Speed Railway

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The demand for the high-speed fastener inspection technology has increased greatly as the train speed is growing up. A low-cost high-speed fastener inspection system was proposed in this paper. By using motion image and direction field, the proposed inspection system takes some advantages of current methods, and has the features of depth insensitive and high contrast with background.Our experimental results show that this system is a potential solution for high-speed fastener inspection.

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738-742

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September 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] C. Mair and S. Fararooy, Practice and potential of computer vision for railways, IEE Seminar. Condition Monitoring for Rail Transport Systems), 1998, p.10/1-10/3.

DOI: 10.1049/ic:19980983

Google Scholar

[2] S. V. Sawadisavi, R. Edwards, E. Resendiz, J. M. Hart, C. P. L. Barkan, and N. Ahuja, Machine-Vision Inspection of Railroad Track, in Transportation Research Board 88th Annual Meeting, 2009, p. 19p.

Google Scholar

[3] P. De Ruvo, A. Distante, E. Stella, and F. Marino, A GPU-based vision system for real time detection of fastening elements in railway inspection, in 2009 IEEE Int. Conf. Image Processing (ICIP), pp.2333-2336.

DOI: 10.1109/icip.2009.5414438

Google Scholar

[4] P. L. Mazzeo, M. Nitti, E. Stella, and A. Distante, Visual recognition of fastening bolts for railroad maintenance, Pattern Recognition Letters, vol. 25, pp.669-677, (2004).

DOI: 10.1016/j.patrec.2004.01.008

Google Scholar

[5] F. Marino, A. Distante, M. Pier Luigi, and E. Stella, A Real-Time Visual Inspection System for Railway Maintenance: Automatic Hexagonal-Headed Bolts Detection, IEEE Transactions. Systems, Man, and Cybernetics, Part C: Applications and Reviews, vol. 37, pp.418-428, (2007).

DOI: 10.1109/tsmcc.2007.893278

Google Scholar

[6] E. Stella, P. Mazzeo, M. Nitti, G. Cicirelli, A. Distante, and T. D'Orazio, Visual recognition of missing fastening elements for railroad maintenance, in 2002 IEEE Int. Conf. Intelligent Transportation Systems, 2002, pp.94-99.

DOI: 10.1109/itsc.2002.1041195

Google Scholar

[7] K. George, H. Herman, S. Sanjiv, T. John, and K. William, Automatic Railway Classification Using Surface and Subsurface Measurements, in International Conference on Field and Service Robotics, 2001, pp.43-48.

Google Scholar

[8] C. Alippi, E. Casagrande, M. Fumagalli, F. Scotti, V. Piuri, and L. Valsecchi, An embedded system methodology for real-time analysis of railways track profile, in 2002 IEEE Int. Conf. Instrumentation and Measurement Technology Conference, IMTC/2002, pp.747-751.

DOI: 10.1109/imtc.2002.1006935

Google Scholar

[9] ENSCO Inc., Track Geometry Measurement System, 2010, Available: http: /www. ensco. com/Track-Geometry-Measurement.

Google Scholar

[10] Rao, A. R. and B. G. Schunck (1989). Computing oriented texture fields. Computer Vision and Pattern Recognition, 1989. Proceedings CVPR '89., IEEE Computer Society Conference on.

DOI: 10.1109/cvpr.1989.37829

Google Scholar

[11] W. Shou-Der and L. Shang-Hong, Fast Template Matching Based on Normalized Cross Correlation With Adaptive Multilevel Winner Update, IEEE Transactions. Image Processing, vol. 17, pp.2227-2235, (2008).

DOI: 10.1109/tip.2008.2004615

Google Scholar