TITLE:
An Application of Canny Edge Detection Algorithm to Rail Thermal Image Fault Detection
AUTHORS:
Libo Cai, Yu Ma, Tangming Yuan, Haifeng Wang, Tianhua Xu
KEYWORDS:
Fault Detection, Rail Thermal Image, Canny Edge Detection, Linear Least Squares
JOURNAL NAME:
Journal of Computer and Communications,
Vol.3 No.11,
November
19,
2015
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.