Roundabouts

Extracted Roundabouts from high-resolution aerial images. Image credit: Mehdi Ravanbakhsh

A new approach for the automatic extraction of road junctions from high resolution aerial images by using an existing topographic database is developed by Dr. Mehdi Ravanbakhsh, a photogrammetry researcher at the University of Melbourne, Australia. He models the road junctions as area objects with considering possible presence of traffic islands and develops an approach that combines a road extraction method with a novel snake model to capture the junction outline. The information that is derived from the geospatial database includes geometric, radiometric, and topological characteristics of junctions. This information gives a rough idea of the junction and guides later processing steps. 

Edges are detected and road segment hypotheses are generated using several geometric and radiometric criteria. Furthermore, road markings if present in the scene are detected in order to verify the obtained road segments. Road  arms are obtained after road segments with similar geometric properties are linked. The resulting road arms supply initial conditions for the snake model.

A novel snake model that employs the ziplock snake concept is proposed. Its external force field is a combination of the balloon force and the GVF (Gradient Vector Flow). Furthermore, the balloon force is associated with the junction shape features incorporated into our snake model implicitly. The GVF increases the capture range of snakes to draw deforming curves from far distances. The balloon force helps to overcome high variation of curvature in the junction border and lack of sufficient contrast between the junction central area and the surrounding. Before snake optimization starts, initial snakes are modified based on the junction geometrical shape to assure a  close initialization. The junction outline is delineated without being overly affected by various kinds of disturbances due to the strong internal snake energy. The obtained junction outline defines an area within which possibly traffic islands exist.

A level set approach is used to detect islands. The initial level set function is constructed from the segmented image. In order to ensure that the evolved curves will converge to the island boundaries, some geometric and topological constraints are introduced based on the characteristics of traffic islands.  This type of initialization and evolution strategy, however, is not effective for roundabouts. Instead, the central island of a roundabout is detected using level sets with a hybrid evolution strategy. This hybrid strategy includes two steps: shrinking and iterative expansion curve evolution. Eventually, the central island is obtained after some post-processing. Since the shape of roundabouts is heavily affected by the shape of its central island, we need initially to detect the central island based on which the snake’s external force field is modified. The snake’s external force field is modified using the GVF of a signed distance function. The modified external force field  is intended to pull the snakes toward the roundabout outline regardless of where they are located initially. The reason is that force arrows at any location on the modified force field point to the roundabout outline.

Source: Ravanbakhsh, M., 2008. Road junction extraction from high resolution aerial imagery assisted by topographic database information. PhD thesis, Leibniz Universität Hannover, Germany, No. 273

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