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Proceedings Paper

Road extraction from high resolution remote sensing image based on mathematics morphology
Author(s): Hongbin Ma; Yahong Zhao; Yongsheng Chen
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Paper Abstract

Extracting target information from the remote sensing images has been becoming an important method of updating the spatial geography data. With the development of spatial technology, sensor technology, digital image processing technology and the computer pattern recognition technology, how to extract target information from the high resolution remote sensing images has become the target of many researchers. Based on the feasibility experimental study of road extraction using Mathematics Morphology, this paper put forward one kind of road extraction method with Mathematics Morphology as primarily path and seed growing as auxiliary path. City road network information in high resolution remote sensing image is taken as the research object. In this paper Mathematics Morphology method and the segment method of Support Vector Machine are used. This paper presents that the combination of Mathematics Morphology and seed growing method has priority to Mathematics Morphology or seed growing used respectively, especially has the superiority in extracting the road detail information.

Paper Details

Date Published: 7 November 2008
PDF: 8 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470O (7 November 2008); doi: 10.1117/12.813225
Show Author Affiliations
Hongbin Ma, Northeastern Univ. (China)
Yahong Zhao, Northeastern Univ. (China)
Yongsheng Chen, Northeastern Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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