Automatic Railway Track Element Detection for East-West Route of Addis Ababa LRT
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Date
2015-08
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Addis Ababa University
Abstract
In railways, regular maintenance and inspection of railway track is quiet commonly used
approach to maintain an acceptable level of safety. Such approach is currently done in
most railway companies; ERC will not be a different, using a very laborious, lengthy
and manual work by visually inspecting and visiting test sites with a help of trained
operators. Another approach is to have an automatic train control system where a train
vehicle is completely controlled by a central control system without the need of human
driver intervention since computer-aided machines are less likely to make mistakes than
humans once carefully designed and installed.
In this thesis, an automated system is presented which mitigates the said problem by
detecting a railway track elements (such as fasteners) from a real railway track image
taken by a digital camera that is mounted in the train. Based on the level of difficulty in
the detection problem, suitable combinations of image processing and pattern
recognition methods are applied to achieve high performance automated detection. The
system is primarily based on the Viola-Jones object detection framework Viola and
Jones, but it selects best new Haar wavelet-like features more convenient to the problem
of Addis Ababa Light rail transit track fasteners detection. The performance of the
system is improved by employing an appropriate image pre-processing and performance
evaluation techniques. Accordingly, the system has managed to achieve a 94.6%
detection rate of performance and has a failure rate of 0.11%.
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Keywords
Railway Track, Addis Ababa LRT, East-West Route, Detection