Recognition of Road Junctions Based on Road Classification Method

MA Chao; SUN Qun; CHEN Huanxin; WEN Bowei

doi:10.13203/j.whugis20160073

Volume 41 Issue 9

Sep. 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(9): 1232-1237. > DOI: 10.13203/j.whugis20160073

MA Chao, SUN Qun, CHEN Huanxin, WEN Bowei. Recognition of Road Junctions Based on Road Classification Method[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1232-1237. DOI: 10.13203/j.whugis20160073

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Recognition of Road Junctions Based on Road Classification Method

1.
Information Engineering University, Zhengzhou 450052, China
2.
96633 Troops, Beijing 100096, China

Funds:

The National 863 Program of China 2012AA12A404

the National Natural Science Foundation of China 41571399

the National Natural Science Foundation of China 41201391

the National Natural Science Foundation of China 41071297

the National Natural Science Foundation of China 41201469

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Author Bio:
MA Chao, PhD candidate, specializes in multi-sourced spatial data fusion and digital mapping. E-mail: jielong018@126.com
Received Date: February 28, 2016
Published Date: September 04, 2016

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Abstract

Abstract

The recognition of microstructures such as road junctions in road networks is of importance for multi-scale road modeling and pedestrian navigation. Aiming to resolve deficiencies in the current recognition methodsfor geometric shape description and shape matching with complex road junctions, the paper presents a road junction recognition method based on the classification of roads and starting with recognition and reduction. Firstly, junctions are located by the node cluster density detection. Then the characteristic vectors are built by analyzing and quantifying the sizes, shapes, and attributes of roads; treating this issue as a two-class classification problem for differentiating main roads and the auxiliary sections, solved by using a support vector machine. Using Open Street Map data for experimental verification, our results show that this method can effectively recognize road junctions.
- road structure recognition,
- road junctions,
- two-class classification,
- support machine vector

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