DocumentCode :
1668272
Title :
Urban road extraction based on hough transform and region growing
Author :
Herumurti, Darlis ; Uchimura, Keiichi ; Koutaki, Gou ; Uemura, Toshifumi
Author_Institution :
Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan
fYear :
2013
Firstpage :
220
Lastpage :
224
Abstract :
In the paper, we present an approach of road extraction in urban area by combining the Hough transform and region growing. In this case, we use Digital Surface Mode (DSM) data, which is based on the elevation of land surface, building, and so on to overcome the disadvantage of aerial photo image. The main problem in extracting the road in urban area from an aerial photo is the shadow cast by the buildings. The shadow will lead to an inappropriate road segment. Another benefit of using the DSM data in urban area is the significant different of the elevation between the road and the building elevation. A simple thresholding of this data could extract some of the road. To improve the result, we use Hough transform to detect and recognize the road as a line and use this information to make a better threshold. Furthermore, we use the seeding region growing method to expand the road network. The seeds for region growing are obtained from the perimeter of the threshold segmentation resulted by hough lines. Finally, the post processing is required to remove a false road by employing the morphology image operator. The experiment result shows that the proposed method improves the quality result with a very good performance.
Keywords :
Hough transforms; automated highways; feature extraction; geophysical image processing; image recognition; image segmentation; mathematical morphology; DSM data; Hough lines; Hough transform; aerial photo image; building elevation; building shadow; data thresholding; digital surface mode data; false road removal; image postprocessing; image quality improvement; image threshold segmentation; morphology image operator; road detection; road network elevation; road recognition; road segment; seeding region growing method; urban road extraction approach; Buildings; Data mining; Image segmentation; Joints; Morphology; Roads; Transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers of Computer Vision, (FCV), 2013 19th Korea-Japan Joint Workshop on
Conference_Location :
Incheon
Print_ISBN :
978-1-4673-5620-6
Type :
conf
DOI :
10.1109/FCV.2013.6485491
Filename :
6485491
Link To Document :
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