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

Libo Cai¹, Yu Ma¹, Tangming Yuan^1*, Haifeng Wang^2*, Tianhua Xu³

¹Department of Computer Science, University of York, Heslington, York, UK.
²National Engineering Research Center of Rail Transportation Operation and Control Systems, Beijing Jiaotong University, Beijing, China.
³Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China.

DOI: 10.4236/jcc.2015.311004                

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.

Keywords

Fault Detection, Rail Thermal Image, Canny Edge Detection, Linear Least Squares

Conflicts of Interest

The authors declare no conflicts of interest.

References

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