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- W2117634434 abstract "Road junctions are important components of a road network. However, they are usually not explicitly modeled in existing road extraction approaches. In this research, we model road junctions in detail as area objects and propose a methodology for their automatic extraction through the use of existing geospatial data. Prior knowledge derived from the geospatial data is used to facilitate the extraction. We define a circular region around the junction center to assure accurate and reliable results. The approach is tested using black and white images of 0.4 m ground resolution taken from open rural areas. Extraction results are represented in order to illustrate different steps of the method and to prove its feasibility." @default.
- W2117634434 created "2016-06-24" @default.
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- W2117634434 date "2007-04-01" @default.
- W2117634434 modified "2023-09-23" @default.
- W2117634434 title "Knowledge-based road junction extraction from high-resolution aerial images" @default.
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- W2117634434 doi "https://doi.org/10.1109/urs.2007.371844" @default.
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