Road Marker Classification Using Geometrical Features With Slope Contour
Driving down and up the roads requires safe manoeuvre to avoid collisions or congestions, subject to the traffic and road conditions, which are regulated by the road markers painted along the roads. As the research in the road lane departures for intelligent transport systems gains huge interest in...
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| Format: | Thesis |
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2019
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| Summary: | Driving down and up the roads requires safe manoeuvre to avoid collisions or congestions, subject to the traffic and road conditions, which are regulated by the road markers painted along the roads. As the research in the road lane departures for intelligent transport systems gains huge interest in the research community, the road markers classification becomes essential. One of the challenges in road marker classification is the varying locations of the road markers between different areas and countries. When classification is carried out using the existing methods, the road marker type transition causes relatively significant errors and delays as compared with the classification over the road stretch without road marker type transitions. Furthermore, the road marker types which look alike such as the dashed-solid (DS) and solid-dashed (SD), are observed to be easily confused, causing more detection failures than the other road marker types. In order to address these problems, an improved camera positioning method to identify a customised area for the Region of Interest (ROI) has been proposed by using the reference of the Field of View (FOV). In addition to the existing five road marker types, namely, Single Solid (SS), Double Solid (DD), Dashed (D), Solid-Dashed (SD) and Dashed-Solid (DS), three novel twolayer classification algorithms were proposed. This was done by virtue of relatively small ROI identified from the road images which were captured by vehicle-mounted cameras. |
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