Obstacle detection over rails using Hough transform
Abstract:
Autonomous systems can assist humans in the important task of
safe driving. Such systems can warn people about possible risks, take actions
to avoid accidents or guide the vehicle without human supervision. Whether in
cars or trains or ships the artificial vision algorithms offer an alternative
for the design and implementation of autonomous driving systems. In railway
scenarios cameras in front of the train can assist drivers with the
identification of obstacles or strange objects on the rails. Multiple factors
add huge complexity to this task. The changing conditions create a scene where
background is hard to detect, lighting varies and process speed must be fast.
This article describes a first approximation to the problem where using the
Hough transform, the rails and area of interest are detected. On this area a
systematic search is done for finding and delimiting possible
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