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Remote Sensing
Article . 2014 . Peer-reviewed
License: CC BY
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Remote Sensing
Article
License: CC BY
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Remote Sensing
Article . 2014
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Automatic Road Centerline Extraction from Imagery Using Road GPS Data

Authors: Chuqing Cao; Ying Sun 0001;

Automatic Road Centerline Extraction from Imagery Using Road GPS Data

Abstract

Road centerline extraction from imagery constitutes a key element in numerous geospatial applications, which has been addressed through a variety of approaches. However, most of the existing methods are not capable of dealing with challenges such as different road shapes, complex scenes, and variable resolutions. This paper presents a novel method for road centerline extraction from imagery in a fully automatic approach that addresses the aforementioned challenges by exploiting road GPS data. The proposed method combines road color feature with road GPS data to detect road centerline seed points. After global alignment of road GPS data, a novel road centerline extraction algorithm is developed to extract each individual road centerline in local regions. Through road connection, road centerline network is generated as the final output. Extensive experiments demonstrate that our proposed method can rapidly and accurately extract road centerline from remotely sensed imagery.

Keywords

road connection, remote sensing, Science, road centerline extraction, satellite image, Q, road GPS data

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Top 10%
Top 10%
gold