An Application of Canny Edge Detection Algorithm to Rail Thermal Image Fault Detection

DOI: 10.4236/jcc.2015.311004   PDF   HTML   XML   2,466 Downloads   3,334 Views   Citations

Abstract

The paper discusses an application for rail track thermal image fault detection. In order to get better results from the Canny edge detection algorithm, the image needs to be processed in advance. The histogram equalization method is proposed to enhance the contrast of the image. Since a thermal image contains multiple parallel rail tracks, an algorithm has been developed to locate and separate the tracks that we are interested in. This is accomplished by applying the least squares linear fitting technique to represent the surface of a track. The performance of the application is evaluated by using a number of images provided by a specialised company and the results are essentially favourable.

Share and Cite:

Cai, L. , Ma, Y. , Yuan, T. , Wang, H. and Xu, T. (2015) An Application of Canny Edge Detection Algorithm to Rail Thermal Image Fault Detection. Journal of Computer and Communications, 3, 19-24. doi: 10.4236/jcc.2015.311004.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Clark, R. (2004) Rail Flaw Detection: Overview and Needs for Future Developments. NDTE International Independent Nondestructive Testing and Evaluation, 37, 111-118. http://dx.doi.org/10.1016/j.ndteint.2003.06.002
[2] Peng, D. and Jones, R. (2013) NDI of Rail Squats and Estimating Defect Size and Location Using Lock-In Thermography. Engineering, 5, 29-38. http://dx.doi.org/10.4236/eng.2013.51005
[3] Deutschl, E., et al. (2004) Defect Detection on Rail Surfaces by a Vision Based System. IEEE Intelligent Vehicles Symposium, 507-511. http://dx.doi.org/10.1109/ivs.2004.1336435
[4] Canny, J. (1986) A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 679-698. http://dx.doi.org/10.1109/TPAMI.1986.4767851
[5] Parker, J.R. (2010) Algorithms for Image Processing and Computer Vision. 2nd Edition, John Wiley & Sons.
[6] Gonzalez, R. and Woods, R. (2008) Digital Image Processing. 3rd Edition, Prentice Hall.
[7] Freedman, D. (2009) Statistical Models: Theory and Practice. Revised Edition, Cambridge University Press. http://dx.doi.org/10.1017/CBO9780511815867
[8] Cai, L., et al. (2005) Railway Track Thermal Analyzer System Maintenance Manual. MSc Software Engineering Team Project Group Report, University of York.

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.