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Pothole Detection Using Computer Vision and Learning
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DOI：10.1109/TITS.2019.2931297.png)
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Techniques for identifying potholes on road surfaces aim at developing strategies for real-time or offline identification of potholes, to support real-time control of a vehicle (for driver assistance or autonomous driving) or offline data collection for road maintenance. For these reasons, research around the world has comprehensively explored strategies for the identification of potholes on roads. This paper starts with a brief review of the field; it classifies developed strategies into several categories. We, then, present our contributions to this field by implementing strategies for automatic identification of potholes. We developed and studied two techniques based on stereo-vision analysis of road environments ahead of the vehicle; we also designed two models for deep-learning-based pothole detection. An experimental evaluation of those four designed methods is provided, and conclusions are drawn about particular benefits of these methods.
Keyword:
Roads
Three-dimensional displays
Image reconstruction
Shape
Two dimensional displays
Accelerometers
Cameras
Pothole detection
stereo vision
deep learning
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