access icon free Junction-aware water flow approach for urban road network extraction

The highways now offer more and more complex road junctions composed of many surrounding roads, overlapping each other with high curvature. Traditional road detection methods are not adequate for the rapid development of cities with increased complexity of the road junction shape. The major challenges in road extraction are varying spectral reflectance, lane markings, obstacles with different sizes, of various shapes, and intersected roads. However, very few researchers have attempted handling overlapped roads with low curvature only. In this study, a water flow-based semi-automatic approach is proposed for extracting road network with various shapes of junctions (Y-shaped with different acute angles), intersected and also for overlapped high curvilinear roads. Recognising the complex road junction is done with fewer automatically generated anchor points without human intervention, which detects the number of roads (branches) connected to that junction along the road's width, orientation and length with less computation time. Hence, from a manually selected seed point, the authors' algorithm can be automatically propagated throughout a whole road network with or without single lane or multiple lanes (lined, dotted or both). Experimental results show that this proposed approach can accurately and efficiently extract interconnected road network from QuickBird images with minimal seed points.

Inspec keywords: remote sensing; feature extraction; image recognition; geophysical image processing; roads

Other keywords: road junction shape; junction-aware water flow approach; water flow-based semiautomatic approach; interconnected road network; urban road network extraction; overlapped high curvilinear roads; road intersection; remote sensing images; seed point; very high resolution QuickBird images; road junction recognition

Subjects: Data and information; acquisition, processing, storage and dissemination in geophysics; Computer vision and image processing techniques; Geography and cartography computing; Other topics in Earth sciences; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Image recognition

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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2015.0263
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