7 November 2008 Semi-automatic extraction of ribbon roads from high resolution remotely sensed imagery by T-shaped template matching
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Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470J (2008); doi: 10.1117/12.813220
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
In this paper, we present a novel approach for semi-automatic extraction of ribbon road axes from high resolution remotely sensed imagery. The core of our system is a road tracker based on T-shaped template matching. T-shaped template is composed of a profile perpendicular to the road axis and a rectangle parallel to and as wide as the road marks or strips of vegetation. Actually, the T-shaped template matching is an integration and improvement of typical profile matching and rectangular template matching. At the same time, parabola is deployed to model the road trajectory to predict the position of subsequent road points and to guide the tracking go through bad road conditions. Simultaneously, the least square matching is employed to search the precise road centerline point. Extensive experiments demonstrate that our proposed algorithm can fast and reliably trace roads with road marks or strip of vegetation.
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Xiangguo Lin, Jixian Zhang, Zhengjun Liu, Jing Shen, "Semi-automatic extraction of ribbon roads from high resolution remotely sensed imagery by T-shaped template matching", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470J (7 November 2008); doi: 10.1117/12.813220; https://doi.org/10.1117/12.813220
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KEYWORDS
Roads

Vegetation

Image resolution

Detection and tracking algorithms

Image segmentation

Feature extraction

Remote sensing

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