A research of road centerline extraction algorithm from high resolution remote sensing images

Yushan Zhang; Tingfa Xu

doi:10.1117/12.2271748

19 September 2017 A research of road centerline extraction algorithm from high resolution remote sensing images

Yushan Zhang, Tingfa Xu

Proceedings Volume 10396, Applications of Digital Image Processing XL; 103961W (2017) https://doi.org/10.1117/12.2271748
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images. An intelligent and automatic road extraction algorithm with high precision has great significance for transportation, road network updating and urban planning. The fuzzy c-means (FCM) clustering segmentation algorithms have been used in road extraction, but the traditional algorithms did not consider spatial information. An improved fuzzy C-means clustering algorithm combined with spatial information (SFCM) is proposed in this paper, which is proved to be effective for noisy image segmentation. Firstly, the image is segmented using the SFCM. Secondly, the segmentation result is processed by mathematical morphology to remover the joint region. Thirdly, the road centerlines are extracted by morphology thinning and burr trimming. The average integrity of the centerline extraction algorithm is 97.98%, the average accuracy is 95.36% and the average quality is 93.59%. Experimental results show that the proposed method in this paper is effective for road centerline extraction.

Citation Download Citation

Yushan Zhang and Tingfa Xu "A research of road centerline extraction algorithm from high resolution remote sensing images", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103961W (19 September 2017); https://doi.org/10.1117/12.2271748

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available