JOURNAL ARTICLE

Automatic extraction of road networks from map images

Wataru ItonagaIkuo MatsudaN. YoneyamaShintaro Itoh

Year: 2003 Journal:   Electronics and Communications in Japan (Part II Electronics) Vol: 86 (4)Pages: 62-72   Publisher: Wiley

Abstract

Abstract With the advent of sophisticated and diversified car navigation systems in recent years, it is becoming increasingly important to construct a precise and detailed map database. Among map data, road‐network information is a representation of the connection relations of roads by a graph structure, and is one of the most important kinds of information used in route search and guidance, which is the basic function of car navigation systems. At present, much manpower and time are being spent in the preparation of road‐network information, and it is desirable to reduce the labor required by automation using computers. This paper presents a method in which the road network is automatically extracted from map information. First, the road area is extracted from the map image by stochastic relaxation based on the geometrical properties of the road area and the background area. Then, thinning and piecewise‐linear approximation are applied to the road area to extract the road‐network information, which consists of the graphic structure of nodes and links. In this process, the distortion near junctions produced by thinning is corrected, and the nodes are optimally rearranged so that the road network represents the centers of the roads. Then, precise road‐network information is stably extracted. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 86(4): 62–72, 2003; Published online in Wiley InterScience ( www.interscience. wiley.com ). DOI 10.1002/ecjb.10144

Keywords:
Computer science Artificial intelligence Road map Extraction (chemistry) Computer vision Pattern recognition (psychology) Data mining Geography Cartography

Metrics

6
Cited By
3.36
FWCI (Field Weighted Citation Impact)
0
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Automated Road and Building Extraction
Physical Sciences →  Engineering →  Ocean Engineering
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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