Automatic urban road extraction on DSM data based on fuzzy ART, region growing, morphological operations and radon transform

Darlis Herumurti; Keiichi Uchimura; Gou Koutaki; Takumi Uemura

doi:10.1117/12.2029069

17 October 2013 Automatic urban road extraction on DSM data based on fuzzy ART, region growing, morphological operations and radon transform

Darlis Herumurti, Keiichi Uchimura, Gou Koutaki, Takumi Uemura

Author Affiliations +

Proceedings Volume 8892, Image and Signal Processing for Remote Sensing XIX; 88920A (2013) https://doi.org/10.1117/12.2029069
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

In recent years, an automatic urban road extraction, as part of Intelligent Transportation research, has attracted the researchers due to the important role for the next modern transportation where urban area plays the main role within the transportation system. In this work, we propose a new combination of fuzzy ART clustering, Region growing, Morphological Operations and Radon transform (ARMOR) for automatic extraction of urban road networks from the digital surface model (DSM). The DSM data, which is based-on the elevation of surface, overcome a serious building's shadow problem as in the aerial photo image. Due to the different elevation between the road and the buildings, the thresholding technique yields a fast initial road extraction. The threshold values are obtained from Fuzzy ART clustering of the geometrical points in the histogram. The initial road is then expanded using region growing. Though most of the road regions are extracted, it contains a lot of non-road areas and the edge is still rough. A fast way to smoothing the region is by employing the morphology closing operation. Furthermore, we perform the road line filter by opening operation with a line shape structuring element, where the line orientation is obtained from the Radon Transform. Finally, the road network is constructed based-on B-Spline from the extracted road skeleton. The experimental result shows that the proposed method running faster and increases the quality and the accuracy about 10% higher than the highest result of the compared method.

Citation Download Citation

Darlis Herumurti, Keiichi Uchimura, Gou Koutaki, and Takumi Uemura "Automatic urban road extraction on DSM data based on fuzzy ART, region growing, morphological operations and radon transform", Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 88920A (17 October 2013); https://doi.org/10.1117/12.2029069

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