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4th IEEE Southwest Symposium on Image Analysis and Interpretation
Towards Knowledge-Based Extraction of Roads from 1m-Resolution Satellite Images
Austin, Texas
April 02-April 04
ISBN: 0-7695-0595-3
Hae Yeoun Lee, Korea Advanced Institute of Science and Technology
Heung-Kyu Lee, Korea Advanced Institute of Science and Technology
Tak-gon Kim, Korea Advanced Institute of Science and Technology
Wonkyu Park, Satellite Technology Research Center
As IKONOS satellite with 1m-resolution camera has been launched in 1999, mapping using space-borne images will be a hot issue in computer vision area as well as photogrammetry, mainly because most of major man-made objects of interest can be identifiable. One of the automatically identifiable objects of importance may be a road. Detecting roads using edge detection approaches may be very difficult because a number of edge elements from such as buildings, etc. can be generated from edge detector.In this paper, we propose a method for the extraction of approximated road regions based on region segmentation that utilizes region information. Our method consists of the following three steps. First, an image is segmented using the modified hierarchical multi-scale gradient watershed transformation. Then, the road candidates are identified using information about road, gray level, elongatedness and connectedness. Connecting the close-by roads knowing that roads are connected objects expands the identified road candidates. Our method was tested on the simulated space-borne images and the result shows that the automation of road extraction is quite promising.
Index Terms:
Road extraction, watershed, region adjacency graph, knowledge base, satellite
Citation:
Hae Yeoun Lee, Heung-Kyu Lee, Tak-gon Kim, Wonkyu Park, "Towards Knowledge-Based Extraction of Roads from 1m-Resolution Satellite Images," ssiai, pp.171, 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000
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