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Semi-automatic extraction of road networks is greatly needed to accelerate the acquisition and update of geodata. However, the road surfaces are seriously disturbed by occlusion of vehicles or shadows on high resolution remotely sensed imagery in urban areas, which makes most of road trackers, using least-squares template matching, inefficient. Fortunately, the scale of many disturbing features such...
In this paper, a novel tracker for semi-automatic extraction of ribbon road centerlines from high resolution remotely sensed imagery is proposed. Actually, our approach is an integration of least squares profile matching and least squares rectangular template matching. After initialization, a road template model is built which is composed of two parts: a profile perpendicular to the road axis, and...
Road tracking is a promising technique to increase the efficiency of road mapping. In this paper, a new semi-automatic road tracker, parallel angular texture signature (PATS) is presented. The tracker is object-oriented in some sense, because it makes best use of the texture signature of road primitives on high-resolution remotely sensed imagery. Our tracker uses parabola to model the road trajectory...
Road tracking is a promising technique to increase the efficiency of road mapping. In this paper, a new road tracker, angular texture signature, is proposed based on the knowledge of the roads on high resolution imagery. The tracker uses parabola to model the road trajectory and predict the position of next road centreline point. It employs angular texture signature to get the moving direction of...
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