Title :
An Optimal Road Seed Extraction Algorithm
Author :
Hu, Yang ; Chehdi, Kacem ; Li, Guangyao ; Zu, Keju
Author_Institution :
CAD Res. Center, Tongji Univ., Shanghai
Abstract :
The proper extraction of road seeds is the premier step of road network extraction from high resolution remote sensing images. An optimal road seed extraction algorithm is proposed. Firstly, Canny-Deriche edge detection and spatial FCM (fuzzy c means) region extraction are performed separately to detect the details.Secondly, an averaged Hausdorff distance is introduced to evaluate the difference between the results of the two methods. Thirdly, in order to take advantages of both edge detection and region extraction, some constraints are loosen and each kind of information is corrected and complemented by the other through iterations, until the results are consistent and unnecessary details are eliminated. Finally, road seeds are extracted through iterative Hough Transform and grouping. The proposed algorithm is tested on high resolution Ikonos images and the results are proved to be favorable.
Keywords :
Hough transforms; edge detection; feature extraction; fuzzy set theory; geographic information systems; iterative methods; remote sensing; roads; Canny-Deriche edge detection; Hausdorff distance; Ikonos images; fuzzy c means; high resolution remote sensing images; iterative Hough transform; optimal road seed extraction algorithm; road network extraction; spatial FCM region extraction; Broadband communication; Data mining; Educational technology; Geoscience and remote sensing; Image edge detection; Image resolution; Iterative algorithms; Remote sensing; Roads; Spatial resolution;
Conference_Titel :
Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3563-0
DOI :
10.1109/ETTandGRS.2008.360
